-
Global information
- Generated on Sat Jan 24 04:10:04 2026
- Log file: /project/archive/log/postgres/dbdev51/postgresql.log-20260123
- Parsed 5,603 log entries in 2s
- Log start from 2026-01-18 09:31:21 to 2026-01-23 18:39:25
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Overview
Global Stats
- 13 Number of unique normalized queries
- 25 Number of queries
- 8m44s Total query duration
- 2026-01-18 15:19:40 First query
- 2026-01-22 12:40:57 Last query
- 2 queries/s at 2026-01-18 15:19:40 Query peak
- 8m44s Total query duration
- 0ms Prepare/parse total duration
- 0ms Bind total duration
- 8m44s Execute total duration
- 89 Number of events
- 16 Number of unique normalized events
- 22 Max number of times the same event was reported
- 0 Number of cancellation
- 3 Total number of automatic vacuums
- 8 Total number of automatic analyzes
- 0 Number temporary file
- 0 Max size of temporary file
- 0.00 B Average size of temporary file
- 624 Total number of sessions
- 37 sessions at 2026-01-20 15:48:40 Session peak
- 1056d14h32m22s Total duration of sessions
- 1d16h38m19s Average duration of sessions
- 0 Average queries per session
- 840ms Average queries duration per session
- 1d16h38m18s Average idle time per session
- 634 Total number of connections
- 18 connections/s at 2026-01-18 15:19:33 Connection peak
- 2 Total number of databases
SQL Traffic
Key values
- 2 queries/s Query Peak
- 2026-01-18 15:19:40 Date
SELECT Traffic
Key values
- 2 queries/s Query Peak
- 2026-01-18 15:19:40 Date
INSERT/UPDATE/DELETE Traffic
Key values
- 0 queries/s Query Peak
- Date
Queries duration
Key values
- 8m44s Total query duration
Prepared queries ratio
Key values
- 0.00 Ratio of bind vs prepare
- 0.00 % Ratio between prepared and "usual" statements
General Activity
↑ Back to the top of the General Activity tableDay Hour Count Min duration Max duration Avg duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 18 09 0 0ms 0ms 0ms 0ms 0ms 0ms 11 0 0ms 0ms 0ms 0ms 0ms 0ms 15 13 0ms 42s420ms 12s717ms 50s140ms 50s140ms 50s140ms 16 0 0ms 0ms 0ms 0ms 0ms 0ms Jan 20 10 0 0ms 0ms 0ms 0ms 0ms 0ms 11 0 0ms 0ms 0ms 0ms 0ms 0ms 12 0 0ms 0ms 0ms 0ms 0ms 0ms 13 0 0ms 0ms 0ms 0ms 0ms 0ms 14 0 0ms 0ms 0ms 0ms 0ms 0ms 15 0 0ms 0ms 0ms 0ms 0ms 0ms 16 0 0ms 0ms 0ms 0ms 0ms 0ms 18 0 0ms 0ms 0ms 0ms 0ms 0ms 19 0 0ms 0ms 0ms 0ms 0ms 0ms Jan 21 09 0 0ms 0ms 0ms 0ms 0ms 0ms 10 0 0ms 0ms 0ms 0ms 0ms 0ms 11 0 0ms 0ms 0ms 0ms 0ms 0ms 12 0 0ms 0ms 0ms 0ms 0ms 0ms 13 0 0ms 0ms 0ms 0ms 0ms 0ms 14 1 0ms 5s230ms 5s230ms 5s230ms 5s230ms 5s230ms 15 0 0ms 0ms 0ms 0ms 0ms 0ms 16 0 0ms 0ms 0ms 0ms 0ms 0ms 17 0 0ms 0ms 0ms 0ms 0ms 0ms 18 0 0ms 0ms 0ms 0ms 0ms 0ms 19 0 0ms 0ms 0ms 0ms 0ms 0ms Jan 22 10 2 0ms 1m1s 36s592ms 11s986ms 1m1s 1m1s 11 3 0ms 1m1s 29s740ms 1m1s 1m1s 1m1s 12 6 0ms 1m12s 31s895ms 1m24s 1m28s 1m28s 13 0 0ms 0ms 0ms 0ms 0ms 0ms 14 0 0ms 0ms 0ms 0ms 0ms 0ms 15 0 0ms 0ms 0ms 0ms 0ms 0ms 18 0 0ms 0ms 0ms 0ms 0ms 0ms 19 0 0ms 0ms 0ms 0ms 0ms 0ms Jan 23 09 0 0ms 0ms 0ms 0ms 0ms 0ms 10 0 0ms 0ms 0ms 0ms 0ms 0ms 11 0 0ms 0ms 0ms 0ms 0ms 0ms 13 0 0ms 0ms 0ms 0ms 0ms 0ms 14 0 0ms 0ms 0ms 0ms 0ms 0ms 15 0 0ms 0ms 0ms 0ms 0ms 0ms 16 0 0ms 0ms 0ms 0ms 0ms 0ms 17 0 0ms 0ms 0ms 0ms 0ms 0ms 18 0 0ms 0ms 0ms 0ms 0ms 0ms Day Hour SELECT COPY TO Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 18 09 0 0 0ms 0ms 0ms 0ms 11 0 0 0ms 0ms 0ms 0ms 15 13 0 12s717ms 42s420ms 50s140ms 50s140ms 16 0 0 0ms 0ms 0ms 0ms Jan 20 10 0 0 0ms 0ms 0ms 0ms 11 0 0 0ms 0ms 0ms 0ms 12 0 0 0ms 0ms 0ms 0ms 13 0 0 0ms 0ms 0ms 0ms 14 0 0 0ms 0ms 0ms 0ms 15 0 0 0ms 0ms 0ms 0ms 16 0 0 0ms 0ms 0ms 0ms 18 0 0 0ms 0ms 0ms 0ms 19 0 0 0ms 0ms 0ms 0ms Jan 21 09 0 0 0ms 0ms 0ms 0ms 10 0 0 0ms 0ms 0ms 0ms 11 0 0 0ms 0ms 0ms 0ms 12 0 0 0ms 0ms 0ms 0ms 13 0 0 0ms 0ms 0ms 0ms 14 1 0 5s230ms 0ms 5s230ms 5s230ms 15 0 0 0ms 0ms 0ms 0ms 16 0 0 0ms 0ms 0ms 0ms 17 0 0 0ms 0ms 0ms 0ms 18 0 0 0ms 0ms 0ms 0ms 19 0 0 0ms 0ms 0ms 0ms Jan 22 10 2 0 36s592ms 0ms 11s986ms 1m1s 11 3 0 29s740ms 16s773ms 1m1s 1m1s 12 6 0 31s895ms 11s222ms 1m24s 1m28s 13 0 0 0ms 0ms 0ms 0ms 14 0 0 0ms 0ms 0ms 0ms 15 0 0 0ms 0ms 0ms 0ms 18 0 0 0ms 0ms 0ms 0ms 19 0 0 0ms 0ms 0ms 0ms Jan 23 09 0 0 0ms 0ms 0ms 0ms 10 0 0 0ms 0ms 0ms 0ms 11 0 0 0ms 0ms 0ms 0ms 13 0 0 0ms 0ms 0ms 0ms 14 0 0 0ms 0ms 0ms 0ms 15 0 0 0ms 0ms 0ms 0ms 16 0 0 0ms 0ms 0ms 0ms 17 0 0 0ms 0ms 0ms 0ms 18 0 0 0ms 0ms 0ms 0ms Day Hour INSERT UPDATE DELETE COPY FROM Average Duration Latency Percentile(90) Latency Percentile(95) Latency Percentile(99) Jan 18 09 0 0 0 0 0ms 0ms 0ms 0ms 11 0 0 0 0 0ms 0ms 0ms 0ms 15 0 0 0 0 0ms 0ms 0ms 0ms 16 0 0 0 0 0ms 0ms 0ms 0ms Jan 20 10 0 0 0 0 0ms 0ms 0ms 0ms 11 0 0 0 0 0ms 0ms 0ms 0ms 12 0 0 0 0 0ms 0ms 0ms 0ms 13 0 0 0 0 0ms 0ms 0ms 0ms 14 0 0 0 0 0ms 0ms 0ms 0ms 15 0 0 0 0 0ms 0ms 0ms 0ms 16 0 0 0 0 0ms 0ms 0ms 0ms 18 0 0 0 0 0ms 0ms 0ms 0ms 19 0 0 0 0 0ms 0ms 0ms 0ms Jan 21 09 0 0 0 0 0ms 0ms 0ms 0ms 10 0 0 0 0 0ms 0ms 0ms 0ms 11 0 0 0 0 0ms 0ms 0ms 0ms 12 0 0 0 0 0ms 0ms 0ms 0ms 13 0 0 0 0 0ms 0ms 0ms 0ms 14 0 0 0 0 0ms 0ms 0ms 0ms 15 0 0 0 0 0ms 0ms 0ms 0ms 16 0 0 0 0 0ms 0ms 0ms 0ms 17 0 0 0 0 0ms 0ms 0ms 0ms 18 0 0 0 0 0ms 0ms 0ms 0ms 19 0 0 0 0 0ms 0ms 0ms 0ms Jan 22 10 0 0 0 0 0ms 0ms 0ms 0ms 11 0 0 0 0 0ms 0ms 0ms 0ms 12 0 0 0 0 0ms 0ms 0ms 0ms 13 0 0 0 0 0ms 0ms 0ms 0ms 14 0 0 0 0 0ms 0ms 0ms 0ms 15 0 0 0 0 0ms 0ms 0ms 0ms 18 0 0 0 0 0ms 0ms 0ms 0ms 19 0 0 0 0 0ms 0ms 0ms 0ms Jan 23 09 0 0 0 0 0ms 0ms 0ms 0ms 10 0 0 0 0 0ms 0ms 0ms 0ms 11 0 0 0 0 0ms 0ms 0ms 0ms 13 0 0 0 0 0ms 0ms 0ms 0ms 14 0 0 0 0 0ms 0ms 0ms 0ms 15 0 0 0 0 0ms 0ms 0ms 0ms 16 0 0 0 0 0ms 0ms 0ms 0ms 17 0 0 0 0 0ms 0ms 0ms 0ms 18 0 0 0 0 0ms 0ms 0ms 0ms Day Hour Prepare Bind Bind/Prepare Percentage of prepare Jan 18 09 0 0 0.00 0.00% 11 0 0 0.00 0.00% 15 0 13 13.00 0.00% 16 0 0 0.00 0.00% Jan 20 10 0 0 0.00 0.00% 11 0 0 0.00 0.00% 12 0 0 0.00 0.00% 13 0 0 0.00 0.00% 14 0 0 0.00 0.00% 15 0 0 0.00 0.00% 16 0 0 0.00 0.00% 18 0 0 0.00 0.00% 19 0 0 0.00 0.00% Jan 21 09 0 0 0.00 0.00% 10 0 0 0.00 0.00% 11 0 0 0.00 0.00% 12 0 0 0.00 0.00% 13 0 0 0.00 0.00% 14 0 1 1.00 0.00% 15 0 0 0.00 0.00% 16 0 0 0.00 0.00% 17 0 0 0.00 0.00% 18 0 0 0.00 0.00% 19 0 0 0.00 0.00% Jan 22 10 0 2 2.00 0.00% 11 0 3 3.00 0.00% 12 0 6 6.00 0.00% 13 0 0 0.00 0.00% 14 0 0 0.00 0.00% 15 0 0 0.00 0.00% 18 0 0 0.00 0.00% 19 0 0 0.00 0.00% Jan 23 09 0 0 0.00 0.00% 10 0 0 0.00 0.00% 11 0 0 0.00 0.00% 13 0 0 0.00 0.00% 14 0 0 0.00 0.00% 15 0 0 0.00 0.00% 16 0 0 0.00 0.00% 17 0 0 0.00 0.00% 18 0 0 0.00 0.00% Day Hour Count Average / Second Jan 18 09 0 0.00/s 11 0 0.00/s 15 51 0.01/s 16 0 0.00/s Jan 20 10 38 0.01/s 11 50 0.01/s 12 3 0.00/s 13 54 0.01/s 14 28 0.01/s 15 6 0.00/s 16 10 0.00/s 18 0 0.00/s 19 0 0.00/s Jan 21 09 1 0.00/s 10 1 0.00/s 11 19 0.01/s 12 0 0.00/s 13 64 0.02/s 14 28 0.01/s 15 3 0.00/s 16 1 0.00/s 17 0 0.00/s 18 0 0.00/s 19 0 0.00/s Jan 22 10 100 0.03/s 11 21 0.01/s 12 16 0.00/s 13 30 0.01/s 14 12 0.00/s 15 1 0.00/s 18 0 0.00/s 19 0 0.00/s Jan 23 09 10 0.00/s 10 0 0.00/s 11 0 0.00/s 13 71 0.02/s 14 12 0.00/s 15 1 0.00/s 16 3 0.00/s 17 0 0.00/s 18 0 0.00/s Day Hour Count Average Duration Average idle time Jan 18 09 1 2d20h40m34s 2d20h40m34s 11 3 2d22h21m7s 2d22h21m7s 15 51 19d14h17m53s 19d14h17m50s 16 0 0ms 0ms Jan 20 10 24 14h24m40s 14h24m40s 11 50 8m18s 8m18s 12 3 30m10s 30m10s 13 54 17m44s 17m44s 14 28 12m12s 12m12s 15 5 18m6s 18m6s 16 10 1h9m30s 1h9m30s 18 1 2h37m39s 2h37m39s 19 1 8h32m23s 8h32m23s Jan 21 09 0 0ms 0ms 10 0 0ms 0ms 11 18 8h29m16s 8h29m16s 12 1 1h37m2s 1h37m2s 13 63 19m36s 19m36s 14 28 16m17s 16m17s 15 3 30m10s 30m10s 16 0 0ms 0ms 17 1 7h47m17s 7h47m17s 18 1 4h13m48s 4h13m48s 19 2 5h47m37s 5h47m37s Jan 22 10 100 1h34m43s 1h34m43s 11 12 25m28s 25m21s 12 15 28m14s 28m2s 13 38 51m26s 51m26s 14 12 12m56s 12m56s 15 0 0ms 0ms 18 1 6h14m26s 6h14m26s 19 2 6h18m46s 6h18m46s Jan 23 09 2 17s477ms 17s477ms 10 0 0ms 0ms 11 0 0ms 0ms 13 71 2h40m21s 2h40m21s 14 12 8m58s 8m58s 15 0 0ms 0ms 16 2 3h16m33s 3h16m33s 17 1 2h15m6s 2h15m6s 18 8 7h38m56s 7h38m56s -
Connections
Established Connections
Key values
- 18 connections Connection Peak
- 2026-01-18 15:19:33 Date
Connections per database
Key values
- ctddev51 Main Database
- 634 connections Total
Connections per user
Key values
- pubeu Main User
- 634 connections Total
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Sessions
Simultaneous sessions
Key values
- 37 sessions Session Peak
- 2026-01-20 15:48:40 Date
Histogram of session times
Key values
- 184 60000-600000ms duration
Sessions per database
Key values
- ctddev51 Main Database
- 624 sessions Total
Sessions per user
Key values
- pubeu Main User
- 624 sessions Total
Sessions per host
Key values
- 10.12.5.37 Main Host
- 624 sessions Total
Host Count Total Duration Average Duration 10.12.5.37 497 55d10h1m56s 2h40m34s 10.12.5.38 12 327d21h31m14s 27d7h47m36s 10.12.5.39 12 327d20h1m25s 27d7h40m7s 10.12.5.40 12 327d20h1m34s 27d7h40m7s 10.12.5.56 6 1s319ms 219ms 192.168.201.10 36 5d3h46m13s 3h26m17s 192.168.201.14 45 12d11h9m55s 6h38m53s 192.168.201.6 2 1s492ms 746ms [local] 2 65ms 32ms -
Checkpoints / Restartpoints
Checkpoints Buffers
Key values
- 575 buffers Checkpoint Peak
- 2026-01-21 15:50:31 Date
- 57.694 seconds Highest write time
- 0.006 seconds Sync time
Checkpoints Wal files
Key values
- 0 files Wal files usage Peak
- 2026-01-20 10:19:44 Date
Checkpoints distance
Key values
- 9.85 Mo Distance Peak
- 2026-01-21 15:50:31 Date
Checkpoints Activity
↑ Back to the top of the Checkpoint Activity tableDay Hour Written buffers Write time Sync time Total time Jan 18 09 0 0s 0s 0s 11 0 0s 0s 0s 15 14 1.506s 0.003s 1.563s 16 51 5.103s 0.001s 5.118s Jan 20 10 486 48.917s 0.003s 48.969s 11 12 1.304s 0.005s 1.347s 12 0 0s 0s 0s 13 0 0s 0s 0s 14 202 20.506s 0.002s 20.537s 15 182 18.513s 0.006s 18.571s 16 24 2.489s 0.001s 2.505s 18 0 0s 0s 0s 19 0 0s 0s 0s Jan 21 09 181 18.245s 0.001s 18.261s 10 89 8.995s 0.001s 9.011s 11 0 0s 0s 0s 12 0 0s 0s 0s 13 0 0s 0s 0s 14 290 29.136s 0.001s 29.151s 15 575 57.694s 0.002s 57.71s 16 11 1.18s 0.001s 1.196s 17 1 0.306s 0.001s 0.321s 18 0 0s 0s 0s 19 0 0s 0s 0s Jan 22 10 7 0.794s 0.001s 0.81s 11 0 0s 0s 0s 12 14 1.51s 0.001s 1.525s 13 0 0s 0s 0s 14 0 0s 0s 0s 15 182 18.336s 0.003s 18.395s 18 0 0s 0s 0s 19 0 0s 0s 0s Jan 23 09 0 0s 0s 0s 10 58 5.917s 0.004s 5.941s 11 51 5.221s 0.006s 5.308s 13 5 0.574s 0.001s 0.589s 14 0 0s 0s 0s 15 3 0.519s 0.001s 0.536s 16 53 5.395s 0.004s 5.454s 17 0 0s 0s 0s 18 0 0s 0s 0s Day Hour Added Removed Recycled Synced files Longest sync Average sync Jan 18 09 0 0 0 0 0s 0s 11 0 0 0 0 0s 0s 15 0 1 0 12 0.001s 0.002s 16 0 0 0 9 0.001s 0.001s Jan 20 10 0 0 0 100 0.001s 0.002s 11 0 0 0 27 0.001s 0.001s 12 0 0 0 0 0s 0s 13 0 0 0 0 0s 0s 14 0 0 0 23 0.001s 0.002s 15 0 0 0 23 0.001s 0.002s 16 0 0 0 7 0.001s 0.001s 18 0 0 0 0 0s 0s 19 0 0 0 0 0s 0s Jan 21 09 0 0 0 76 0.001s 0.001s 10 0 0 0 60 0.001s 0.001s 11 0 0 0 0 0s 0s 12 0 0 0 0 0s 0s 13 0 0 0 0 0s 0s 14 0 0 0 20 0.001s 0.001s 15 0 0 0 17 0.001s 0.001s 16 0 0 0 7 0.001s 0.001s 17 0 0 0 1 0.001s 0.001s 18 0 0 0 0 0s 0s 19 0 0 0 0 0s 0s Jan 22 10 0 0 0 6 0.001s 0.001s 11 0 0 0 0 0s 0s 12 0 0 0 10 0.001s 0.001s 13 0 0 0 0 0s 0s 14 0 0 0 0 0s 0s 15 0 0 0 50 0.001s 0.001s 18 0 0 0 0 0s 0s 19 0 0 0 0 0s 0s Jan 23 09 0 0 0 0 0s 0s 10 0 0 0 48 0.001s 0.001s 11 0 0 0 54 0.001s 0.001s 13 0 0 0 5 0.001s 0.001s 14 0 0 0 0 0s 0s 15 0 0 0 2 0.001s 0.001s 16 0 0 0 47 0.001s 0.001s 17 0 0 0 0 0s 0s 18 0 0 0 0 0s 0s Day Hour Count Avg time (sec) Jan 18 09 0 0s 11 0 0s 15 0 0s 16 0 0s Jan 20 10 0 0s 11 0 0s 12 0 0s 13 0 0s 14 0 0s 15 0 0s 16 0 0s 18 0 0s 19 0 0s Jan 21 09 0 0s 10 0 0s 11 0 0s 12 0 0s 13 0 0s 14 0 0s 15 0 0s 16 0 0s 17 0 0s 18 0 0s 19 0 0s Jan 22 10 0 0s 11 0 0s 12 0 0s 13 0 0s 14 0 0s 15 0 0s 18 0 0s 19 0 0s Jan 23 09 0 0s 10 0 0s 11 0 0s 13 0 0s 14 0 0s 15 0 0s 16 0 0s 17 0 0s 18 0 0s Day Hour Mean distance Mean estimate Jan 18 09 0.00 kB 0.00 kB 11 0.00 kB 0.00 kB 15 22.67 kB 10,081.00 kB 16 225.00 kB 225.00 kB Jan 20 10 846.00 kB 846.00 kB 11 63.00 kB 829.00 kB 12 0.00 kB 0.00 kB 13 0.00 kB 0.00 kB 14 186.00 kB 728.50 kB 15 38.50 kB 612.50 kB 16 30.00 kB 526.00 kB 18 0.00 kB 0.00 kB 19 0.00 kB 0.00 kB Jan 21 09 1,033.00 kB 1,033.00 kB 10 515.00 kB 981.00 kB 11 0.00 kB 0.00 kB 12 0.00 kB 0.00 kB 13 0.00 kB 0.00 kB 14 2,712.00 kB 2,712.00 kB 15 5,044.00 kB 5,044.00 kB 16 22.00 kB 4,542.00 kB 17 5.00 kB 4,088.00 kB 18 0.00 kB 0.00 kB 19 0.00 kB 0.00 kB Jan 22 10 31.00 kB 3,683.00 kB 11 0.00 kB 0.00 kB 12 21.00 kB 3,316.00 kB 13 0.00 kB 0.00 kB 14 0.00 kB 0.00 kB 15 1,025.00 kB 3,087.00 kB 18 0.00 kB 0.00 kB 19 0.00 kB 0.00 kB Jan 23 09 0.00 kB 0.00 kB 10 423.00 kB 2,821.00 kB 11 541.00 kB 2,593.00 kB 13 11.00 kB 2,335.00 kB 14 0.00 kB 0.00 kB 15 7.00 kB 2,102.00 kB 16 271.00 kB 1,919.00 kB 17 0.00 kB 0.00 kB 18 0.00 kB 0.00 kB -
Temporary Files
Size of temporary files
Key values
- 0 Temp Files size Peak
- Date
Size of temporary files (5 minutes period)
NO DATASET
Number of temporary files
Key values
- 0 per second Temp Files Peak
- Date
Number of temporary files (5 minutes period)
NO DATASET
Temporary Files Activity
↑ Back to the top of the Temporary Files Activity tableDay Hour Count Total size Average size Jan 18 09 0 0 0 11 0 0 0 15 0 0 0 16 0 0 0 Jan 20 10 0 0 0 11 0 0 0 12 0 0 0 13 0 0 0 14 0 0 0 15 0 0 0 16 0 0 0 18 0 0 0 19 0 0 0 Jan 21 09 0 0 0 10 0 0 0 11 0 0 0 12 0 0 0 13 0 0 0 14 0 0 0 15 0 0 0 16 0 0 0 17 0 0 0 18 0 0 0 19 0 0 0 Jan 22 10 0 0 0 11 0 0 0 12 0 0 0 13 0 0 0 14 0 0 0 15 0 0 0 18 0 0 0 19 0 0 0 Jan 23 09 0 0 0 10 0 0 0 11 0 0 0 13 0 0 0 14 0 0 0 15 0 0 0 16 0 0 0 17 0 0 0 18 0 0 0 -
Vacuums
Vacuums / Analyzes Distribution
Key values
- 0.01 sec Highest CPU-cost vacuum
Table pg_catalog.pg_class
Database ctddev51 - 2026-01-20 10:23:57 Date
- 0 sec Highest CPU-cost analyze
Table
Database ctddev51 - Date
Average Autovacuum Duration
Key values
- 0.01 sec Highest CPU-cost vacuum
Table pg_catalog.pg_class
Database ctddev51 - 2026-01-20 10:23:57 Date
Analyzes per table
Key values
- pg_catalog.pg_class (3) Main table analyzed (database ctddev51)
- 8 analyzes Total
Vacuums per table
Key values
- pub2.chem_conc_anatomy (1) Main table vacuumed on database ctddev51
- 3 vacuums Total
Tuples removed per table
Key values
- pg_catalog.pg_class (78) Main table with removed tuples on database ctddev51
- 78 tuples Total removed
Pages removed per table
Key values
- unknown (0) Main table with removed pages on database unknown
- 0 pages Total removed
Autovacuum Activity
↑ Back to the top of the Autovacuum Activity tableDay Hour VACUUMs ANALYZEs Jan 18 09 0 0 11 0 0 15 0 0 16 0 0 Jan 20 10 1 4 11 0 0 12 0 0 13 0 0 14 0 1 15 0 0 16 0 0 18 0 0 19 0 0 Jan 21 09 0 0 10 0 0 11 0 0 12 0 0 13 0 0 14 1 1 15 1 1 16 0 0 17 0 0 18 0 0 19 0 0 Jan 22 10 0 0 11 0 0 12 0 0 13 0 0 14 0 0 15 0 1 18 0 0 19 0 0 Jan 23 09 0 0 10 0 0 11 0 0 13 0 0 14 0 0 15 0 0 16 0 0 17 0 0 18 0 0 - 0.01 sec Highest CPU-cost vacuum
-
Locks
Locks by types
Key values
- unknown Main Lock Type
- 0 locks Total
Most frequent waiting queries (N)
Rank Count Total time Min time Max time Avg duration Query NO DATASET
Queries that waited the most
Rank Wait time Query NO DATASET
-
Queries
Queries by type
Key values
- 25 Total read queries
- 0 Total write queries
Queries by database
Key values
- unknown Main database
- 13 Requests
- 7m4s (unknown)
- Main time consuming database
Queries by user
Key values
- unknown Main user
- 13 Requests
User Request type Count Duration edit Total 4 40s994ms select 4 40s994ms editeu Total 4 28s928ms select 4 28s928ms pubeu Total 4 29s847ms select 4 29s847ms unknown Total 13 7m4s select 13 7m4s Duration by user
Key values
- 7m4s (unknown) Main time consuming user
User Request type Count Duration edit Total 4 40s994ms select 4 40s994ms editeu Total 4 28s928ms select 4 28s928ms pubeu Total 4 29s847ms select 4 29s847ms unknown Total 13 7m4s select 13 7m4s Queries by host
Key values
- unknown Main host
- 25 Requests
- 8m44s (unknown)
- Main time consuming host
Queries by application
Key values
- unknown Main application
- 25 Requests
- 8m44s (unknown)
- Main time consuming application
Number of cancelled queries
Key values
- 0 per second Cancelled query Peak
- 2026-01-22 15:43:00 Date
Number of cancelled queries (5 minutes period)
NO DATASET
-
Top Queries
Histogram of query times
Key values
- 14 > 10000ms duration
Slowest individual queries
Rank Duration Query 1 1m12s select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;[ Date: 2026-01-22 12:40:38 - Bind query: yes ]
2 1m6s select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;[ Date: 2026-01-22 12:31:39 - Bind query: yes ]
3 1m1s select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;[ Date: 2026-01-22 11:06:47 - Bind query: yes ]
4 1m1s select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;[ Date: 2026-01-22 10:59:56 - Bind query: yes ]
5 42s420ms SELECT /* AdvancedIxnQueryDAO.getData */ g.nm geneSymbol, g.id geneId, g.acc_txt geneAcc, g.acc_db_cd geneAccDbCd, c.nm chemNm, c.nm_html chemNmhtml, c.acc_txt chemAcc, c.secondary_nm casRN, c.id chemId, i.id ixnId, i.ixn_prose_txt ixnProse, i.ixn_prose_html ixnProseHtml, i.actions_txt ixnActions, COUNT(DISTINCT gcr.reference_id) refCount, COUNT(DISTINCT gcr.taxon_id) taxonCount, COUNT(*) OVER () fullRowCount FROM gene_chem_reference gcr INNER JOIN ixn i ON gcr.ixn_id = i.id INNER JOIN term g ON gcr.gene_id = g.id INNER JOIN term c ON gcr.chem_id = c.id WHERE /* CIQH.getIxnWhereCore */ gcr.gene_id = ANY (ARRAY (( SELECT /* IQH.getMasterPathwayWhereEquals.Name */ tp.term_id FROM term_pathway tp WHERE UPPER(tp.pathway_nm) LIKE 'METABOLISM' AND tp.object_type_id = 4))) AND gcr.id IN ( SELECT gcra.gene_chem_reference_id FROM gene_chem_reference_axn gcra WHERE (gcra.action_degree_type_nm = 'increases')) GROUP BY g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id ORDER BY g.nm_sort, c.nm_sort, i.sort_txt LIMIT 50;[ Date: 2026-01-18 15:51:30 - Bind query: yes ]
6 37s257ms SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterGoWhereEquals.Gene */ ai.gene_id FROM dag_path pi INNER JOIN gene_go_annot ai ON pi.descendant_object_id = ai.go_term_id INNER JOIN term_label li ON li.term_id = pi.ancestor_object_id WHERE UPPER(li.nm) LIKE 'APOPTOSIS' AND li.object_type_id = 5)) ORDER BY g.nm_sort, g.id LIMIT 50;[ Date: 2026-01-18 15:50:18 - Bind query: yes ]
7 17s837ms select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;[ Date: 2026-01-22 12:31:59 - Bind query: yes ]
8 16s773ms select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;[ Date: 2026-01-22 11:07:05 - Bind query: yes ]
9 16s651ms select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;[ Date: 2026-01-22 12:40:57 - Bind query: yes ]
10 15s712ms select distinct /* ChemPhenotypesAssnsDAO */ associatedTerm.nm || '^' || o.cd || '^' || associatedTerm.nm_html || '^' || associatedTerm.acc_txt || '^' || associatedTerm.acc_db_cd as associatedTerm, associatedTerm.id associatedTermId, ptr.ixn_id ixnId, associatedTerm.object_type_id || '|' || associatedTerm.nm_sort associatedTermNmSort, COALESCE(associatedTerm.secondary_nm, '') casRN, phenotypeTerm.nm || '^' || 'go' || '^' || phenotypeTerm.nm_html || '^' || phenotypeTerm.acc_txt || '^' || phenotypeTerm.acc_db_cd as phenotype, phenotypeTerm.id phenotypeId, ( SELECT STRING_AGG(distinct taxonTerm.nm || '^' || 'taxon' || '^' || taxonTerm.nm_html || '^' || taxonTerm.acc_txt || '^' || taxonTerm.acc_db_cd || '^' || COALESCE(taxonTerm.secondary_nm, ''), '|')) as taxonTerms, ( SELECT STRING_AGG(distinct anatomyTerm.nm_html || '^' || anatomyTerm.acc_txt || '^' || ia.level_seq || '^' || anatomyTerm.acc_db_cd || '^' || anatomyTerm.nm, '|')) as anatomyTerms, COUNT(DISTINCT taxonTerm.nm) taxonCount, i.ixn_prose_html ixnProseHtml, i.ixn_prose_txt ixnProse, i.sort_txt ixnSort, ( SELECT STRING_AGG(distinct r.acc_txt, '|')) as references, COUNT(DISTINCT ptr.reference_id) refCount, pt.indirect_term_qty inferredCount, COUNT(*) OVER () fullRowCount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedTerm on ptr.term_id = associatedTerm.id inner join term phenotypeTerm on ptr.phenotype_id = phenotypeTerm.id left outer join term taxonTerm on ptr.taxon_id = taxonTerm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedTerm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyTerm on ia.anatomy_id = anatomyTerm.id where ptr.term_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 2 and upper(baseTerm.nm) LIKE 'ACETYLCYSTEINE')) and ptr.term_object_type_id = 2 and ptr.phenotype_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 5 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = 'GO:0006979' AND l.type_cd = 'A' AND l.object_type_id = 5))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 10 and upper(baseTerm.nm) LIKE 'CARDIOVASCULAR SYSTEM'))) and taxonTerm.id in ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 1 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = '9605' AND l.type_cd = 'A' AND l.object_type_id = 1))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = 'phenotype' and action_degree_type_nm in ('increases')) group by associatedTerm, associatedTermNmSort, phenotype, casRN, ixnId, ixnProseHtml, ixnProse, ixnSort, associatedTermId, phenotypeId, inferredCount ORDER BY associatedTermNmSort LIMIT 50;[ Date: 2026-01-18 15:54:23 - Bind query: yes ]
11 12s882ms SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Name.Gene */ gd.gene_id FROM term t INNER JOIN dag_path dp ON t.id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(t.nm) LIKE 'ASTHMA' AND t.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;[ Date: 2026-01-18 15:50:31 - Database: ctddev51 - User: pubeu - Bind query: yes ]
12 11s986ms select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 2;[ Date: 2026-01-22 10:58:53 - Database: ctddev51 - User: edit - Bind query: yes ]
13 11s222ms select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 2;[ Date: 2026-01-22 12:39:24 - Database: ctddev51 - User: edit - Bind query: yes ]
14 10s885ms select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 2;[ Date: 2026-01-22 11:05:44 - Database: ctddev51 - User: edit - Bind query: yes ]
15 8s694ms select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;[ Date: 2026-01-18 15:19:42 - Database: ctddev51 - User: editeu - Bind query: yes ]
16 8s327ms select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;[ Date: 2026-01-18 15:19:42 - Database: ctddev51 - User: editeu - Bind query: yes ]
17 6s899ms select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 2;[ Date: 2026-01-22 12:30:31 - Database: ctddev51 - User: edit - Bind query: yes ]
18 6s392ms select count(distinct gene_id) from GENE_TAXON where taxon_id = 569441;[ Date: 2026-01-18 15:19:43 - Database: ctddev51 - User: pubeu - Bind query: yes ]
19 6s302ms select p.ancestor_object_id, p.descendant_object_id from DAG_PATH p where p.descendant_object_id in ( select go_term_id from GENE_GO_ANNOT gga where gga.taxon_id = ( select id from TERM where acc_txt = '9606' and object_type_id = ( select id from OBJECT_TYPE where cd = 'taxon')) AND gga.is_not = 'f') and p.ancestor_object_id NOT in ( SELECT c.id FROM TERM c WHERE c.acc_txt in ('ALL') AND c.object_type_id = ( select id from OBJECT_TYPE where cd = 'go'));[ Date: 2026-01-18 15:19:54 - Bind query: yes ]
20 6s149ms select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 1 and t.id = l.TERM_ID;[ Date: 2026-01-18 15:19:40 - Database: ctddev51 - User: editeu - Bind query: yes ]
Time consuming queries (N)
Rank Total duration Times executed Min duration Max duration Avg duration Query 1 5m2s 8 6s899ms 1m12s 37s814ms select id, object_type_id, acc_txt, t.acc_db_id, nm, nm_sort, secondary_nm, description, note from load.term t where object_type_id = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 22 10 2 1m13s 36s592ms 11 2 1m12s 36s223ms 12 4 2m36s 39s220ms [ User: edit - Total duration: 40s994ms - Times executed: 4 ]
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:40:38 Duration: 1m12s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:31:39 Duration: 1m6s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 11:06:47 Duration: 1m1s Bind query: yes
2 51s262ms 3 16s651ms 17s837ms 17s87ms select distinct ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm, ( select string_agg(distinct iq.nm, ?)) from edit.ixn i inner join edit.ixn_actor iachem on i.root_id = iachem.ixn_id inner join edit.ixn_actor iadisease on i.root_id = iadisease.ixn_id inner join edit.ixn_action iact on i.root_id = iact.ixn_id inner join edit.action_type at on iact.action_type_id = at.id inner join edit.reference_ixn ri on i.root_id = ri.ixn_id inner join pub2.term chemterm on iachem.acc_txt = chemterm.acc_txt and chemterm.object_type_id = ? inner join pub2.term diseaseterm on iadisease.acc_txt = diseaseterm.acc_txt and diseaseterm.object_type_id = ? left outer join edit.reference_ixn_qualifier riq on ri.id = riq.reference_ixn_id left outer join edit.ixn_qualifier iq on riq.ixn_qualifier_id = iq.id where i.ixn_type_id = ? and iachem.object_type_id = ? and iadisease.object_type_id = ? group by ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jan 22 11 1 16s773ms 16s773ms 12 2 34s488ms 17s244ms -
select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:31:59 Duration: 17s837ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 11:07:05 Duration: 16s773ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:40:57 Duration: 16s651ms Bind query: yes
3 42s420ms 1 42s420ms 42s420ms 42s420ms select g.nm genesymbol, g.id geneid, g.acc_txt geneacc, g.acc_db_cd geneaccdbcd, c.nm chemnm, c.nm_html chemnmhtml, c.acc_txt chemacc, c.secondary_nm casrn, c.id chemid, i.id ixnid, i.ixn_prose_txt ixnprose, i.ixn_prose_html ixnprosehtml, i.actions_txt ixnactions, count(distinct gcr.reference_id) refcount, count(distinct gcr.taxon_id) taxoncount, count(*) over () fullrowcount from gene_chem_reference gcr inner join ixn i on gcr.ixn_id = i.id inner join term g on gcr.gene_id = g.id inner join term c on gcr.chem_id = c.id where gcr.gene_id = any (array (( select tp.term_id from term_pathway tp where upper(tp.pathway_nm) like ? and tp.object_type_id = ?))) and gcr.id in ( select gcra.gene_chem_reference_id from gene_chem_reference_axn gcra where (gcra.action_degree_type_nm = ?)) group by g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id order by g.nm_sort, c.nm_sort, i.sort_txt limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 18 15 1 42s420ms 42s420ms -
SELECT /* AdvancedIxnQueryDAO.getData */ g.nm geneSymbol, g.id geneId, g.acc_txt geneAcc, g.acc_db_cd geneAccDbCd, c.nm chemNm, c.nm_html chemNmhtml, c.acc_txt chemAcc, c.secondary_nm casRN, c.id chemId, i.id ixnId, i.ixn_prose_txt ixnProse, i.ixn_prose_html ixnProseHtml, i.actions_txt ixnActions, COUNT(DISTINCT gcr.reference_id) refCount, COUNT(DISTINCT gcr.taxon_id) taxonCount, COUNT(*) OVER () fullRowCount FROM gene_chem_reference gcr INNER JOIN ixn i ON gcr.ixn_id = i.id INNER JOIN term g ON gcr.gene_id = g.id INNER JOIN term c ON gcr.chem_id = c.id WHERE /* CIQH.getIxnWhereCore */ gcr.gene_id = ANY (ARRAY (( SELECT /* IQH.getMasterPathwayWhereEquals.Name */ tp.term_id FROM term_pathway tp WHERE UPPER(tp.pathway_nm) LIKE 'METABOLISM' AND tp.object_type_id = 4))) AND gcr.id IN ( SELECT gcra.gene_chem_reference_id FROM gene_chem_reference_axn gcra WHERE (gcra.action_degree_type_nm = 'increases')) GROUP BY g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id ORDER BY g.nm_sort, c.nm_sort, i.sort_txt LIMIT 50;
Date: 2026-01-18 15:51:30 Duration: 42s420ms Bind query: yes
4 37s257ms 1 37s257ms 37s257ms 37s257ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select ai.gene_id from dag_path pi inner join gene_go_annot ai on pi.descendant_object_id = ai.go_term_id inner join term_label li on li.term_id = pi.ancestor_object_id where upper(li.nm) like ? and li.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 18 15 1 37s257ms 37s257ms -
SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterGoWhereEquals.Gene */ ai.gene_id FROM dag_path pi INNER JOIN gene_go_annot ai ON pi.descendant_object_id = ai.go_term_id INNER JOIN term_label li ON li.term_id = pi.ancestor_object_id WHERE UPPER(li.nm) LIKE 'APOPTOSIS' AND li.object_type_id = 5)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:18 Duration: 37s257ms Bind query: yes
5 28s928ms 4 5s757ms 8s694ms 7s232ms select t.id, t.object_type_id, t.acc_txt, t.acc_db_cd, t.nm, t.nm_sort, t.secondary_nm, t.description, t.note, l.nm from pub2.term t, pub2.term_label l where t.object_type_id = ? and t.id = l.term_id;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 18 15 4 28s928ms 7s232ms [ User: editeu - Total duration: 28s928ms - Times executed: 4 ]
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s694ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s327ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 1 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:40 Duration: 6s149ms Database: ctddev51 User: editeu Bind query: yes
6 15s712ms 1 15s712ms 15s712ms 15s712ms select distinct associatedterm.nm || ? || o.cd || ? || associatedterm.nm_html || ? || associatedterm.acc_txt || ? || associatedterm.acc_db_cd as associatedterm, associatedterm.id associatedtermid, ptr.ixn_id ixnid, associatedterm.object_type_id || ? || associatedterm.nm_sort associatedtermnmsort, coalesce(associatedterm.secondary_nm, ?) casrn, phenotypeterm.nm || ? || ? || ? || phenotypeterm.nm_html || ? || phenotypeterm.acc_txt || ? || phenotypeterm.acc_db_cd as phenotype, phenotypeterm.id phenotypeid, ( select string_agg(distinct taxonterm.nm || ? || ? || ? || taxonterm.nm_html || ? || taxonterm.acc_txt || ? || taxonterm.acc_db_cd || ? || coalesce(taxonterm.secondary_nm, ?), ?)) as taxonterms, ( select string_agg(distinct anatomyterm.nm_html || ? || anatomyterm.acc_txt || ? || ia.level_seq || ? || anatomyterm.acc_db_cd || ? || anatomyterm.nm, ?)) as anatomyterms, count(distinct taxonterm.nm) taxoncount, i.ixn_prose_html ixnprosehtml, i.ixn_prose_txt ixnprose, i.sort_txt ixnsort, ( select string_agg(distinct r.acc_txt, ?)) as references, count(distinct ptr.reference_id) refcount, pt.indirect_term_qty inferredcount, count(*) over () fullrowcount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedterm on ptr.term_id = associatedterm.id inner join term phenotypeterm on ptr.phenotype_id = phenotypeterm.id left outer join term taxonterm on ptr.taxon_id = taxonterm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedterm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyterm on ia.anatomy_id = anatomyterm.id where ptr.term_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?)) and ptr.term_object_type_id = ? and ptr.phenotype_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?))) and taxonterm.id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = ? and action_degree_type_nm in (...)) group by associatedterm, associatedtermnmsort, phenotype, casrn, ixnid, ixnprosehtml, ixnprose, ixnsort, associatedtermid, phenotypeid, inferredcount order by associatedtermnmsort limit ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 18 15 1 15s712ms 15s712ms -
select distinct /* ChemPhenotypesAssnsDAO */ associatedTerm.nm || '^' || o.cd || '^' || associatedTerm.nm_html || '^' || associatedTerm.acc_txt || '^' || associatedTerm.acc_db_cd as associatedTerm, associatedTerm.id associatedTermId, ptr.ixn_id ixnId, associatedTerm.object_type_id || '|' || associatedTerm.nm_sort associatedTermNmSort, COALESCE(associatedTerm.secondary_nm, '') casRN, phenotypeTerm.nm || '^' || 'go' || '^' || phenotypeTerm.nm_html || '^' || phenotypeTerm.acc_txt || '^' || phenotypeTerm.acc_db_cd as phenotype, phenotypeTerm.id phenotypeId, ( SELECT STRING_AGG(distinct taxonTerm.nm || '^' || 'taxon' || '^' || taxonTerm.nm_html || '^' || taxonTerm.acc_txt || '^' || taxonTerm.acc_db_cd || '^' || COALESCE(taxonTerm.secondary_nm, ''), '|')) as taxonTerms, ( SELECT STRING_AGG(distinct anatomyTerm.nm_html || '^' || anatomyTerm.acc_txt || '^' || ia.level_seq || '^' || anatomyTerm.acc_db_cd || '^' || anatomyTerm.nm, '|')) as anatomyTerms, COUNT(DISTINCT taxonTerm.nm) taxonCount, i.ixn_prose_html ixnProseHtml, i.ixn_prose_txt ixnProse, i.sort_txt ixnSort, ( SELECT STRING_AGG(distinct r.acc_txt, '|')) as references, COUNT(DISTINCT ptr.reference_id) refCount, pt.indirect_term_qty inferredCount, COUNT(*) OVER () fullRowCount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedTerm on ptr.term_id = associatedTerm.id inner join term phenotypeTerm on ptr.phenotype_id = phenotypeTerm.id left outer join term taxonTerm on ptr.taxon_id = taxonTerm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedTerm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyTerm on ia.anatomy_id = anatomyTerm.id where ptr.term_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 2 and upper(baseTerm.nm) LIKE 'ACETYLCYSTEINE')) and ptr.term_object_type_id = 2 and ptr.phenotype_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 5 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = 'GO:0006979' AND l.type_cd = 'A' AND l.object_type_id = 5))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 10 and upper(baseTerm.nm) LIKE 'CARDIOVASCULAR SYSTEM'))) and taxonTerm.id in ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 1 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = '9605' AND l.type_cd = 'A' AND l.object_type_id = 1))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = 'phenotype' and action_degree_type_nm in ('increases')) group by associatedTerm, associatedTermNmSort, phenotype, casRN, ixnId, ixnProseHtml, ixnProse, ixnSort, associatedTermId, phenotypeId, inferredCount ORDER BY associatedTermNmSort LIMIT 50;
Date: 2026-01-18 15:54:23 Duration: 15s712ms Bind query: yes
7 12s882ms 1 12s882ms 12s882ms 12s882ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term t inner join dag_path dp on t.id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(t.nm) like ? and t.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jan 18 15 1 12s882ms 12s882ms [ User: pubeu - Total duration: 12s882ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Name.Gene */ gd.gene_id FROM term t INNER JOIN dag_path dp ON t.id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(t.nm) LIKE 'ASTHMA' AND t.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:31 Duration: 12s882ms Database: ctddev51 User: pubeu Bind query: yes
8 6s392ms 1 6s392ms 6s392ms 6s392ms select count(distinct gene_id) from gene_taxon where taxon_id = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 18 15 1 6s392ms 6s392ms [ User: pubeu - Total duration: 6s392ms - Times executed: 1 ]
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select count(distinct gene_id) from GENE_TAXON where taxon_id = 569441;
Date: 2026-01-18 15:19:43 Duration: 6s392ms Database: ctddev51 User: pubeu Bind query: yes
9 6s302ms 1 6s302ms 6s302ms 6s302ms select p.ancestor_object_id, p.descendant_object_id from dag_path p where p.descendant_object_id in ( select go_term_id from gene_go_annot gga where gga.taxon_id = ( select id from term where acc_txt = ? and object_type_id = ( select id from object_type where cd = ?)) and gga.is_not = ?) and p.ancestor_object_id not in ( select c.id from term c where c.acc_txt in (...) and c.object_type_id = ( select id from object_type where cd = ?));Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 18 15 1 6s302ms 6s302ms -
select p.ancestor_object_id, p.descendant_object_id from DAG_PATH p where p.descendant_object_id in ( select go_term_id from GENE_GO_ANNOT gga where gga.taxon_id = ( select id from TERM where acc_txt = '9606' and object_type_id = ( select id from OBJECT_TYPE where cd = 'taxon')) AND gga.is_not = 'f') and p.ancestor_object_id NOT in ( SELECT c.id FROM TERM c WHERE c.acc_txt in ('ALL') AND c.object_type_id = ( select id from OBJECT_TYPE where cd = 'go'));
Date: 2026-01-18 15:19:54 Duration: 6s302ms Bind query: yes
10 5s341ms 1 5s341ms 5s341ms 5s341ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term_label l inner join dag_path dp on l.term_id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(l.nm) like ? and l.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 18 15 1 5s341ms 5s341ms [ User: pubeu - Total duration: 5s341ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Label.Gene */ gd.gene_id FROM term_label l INNER JOIN dag_path dp ON l.term_id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(l.nm) LIKE 'GLAUCOMA' AND l.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:49:41 Duration: 5s341ms Database: ctddev51 User: pubeu Bind query: yes
11 5s230ms 1 5s230ms 5s230ms 5s230ms select d.abbr dagabbr, d.nm dagnm, gt.level_min_no daglevelmin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pvalcorrected, te.raw_p_val pvalraw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, count(*) over () fullrowcount from term_enrichment te inner join dag_node gt on te.enriched_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where te.term_id = ? and te.enriched_object_type_id = ? order by te.corrected_p_val, d.abbr, gt.nm_sort limit ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 21 14 1 5s230ms 5s230ms [ User: pubeu - Total duration: 5s230ms - Times executed: 1 ]
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SELECT /* ChemGODAO */ d.abbr dagAbbr, d.nm dagNm, gt.level_min_no dagLevelMin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pValCorrected, te.raw_p_val pValRaw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, COUNT(*) OVER () fullRowCount FROM term_enrichment te INNER JOIN dag_node gt ON te.enriched_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE te.term_id = '1334144' AND te.enriched_object_type_id = 5 ORDER BY te.corrected_p_val, d.abbr, gt.nm_sort LIMIT 50;
Date: 2026-01-21 14:20:23 Duration: 5s230ms Database: ctddev51 User: pubeu Bind query: yes
12 5s88ms 1 5s88ms 5s88ms 5s88ms select ? "Input", d.nm "DiseaseName", d.acc_db_cd || ? || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( select string_agg(stm.slim_term_nm, ? order by stm.slim_term_nm) from slim_term_mapping stm where stm.mapped_term_id = d.id) "DiseaseCategories", case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", string_agg(gdr.source_acc_txt, ? order by gdr.source_acc_txt) "OmimIDs", string_agg(distinct r.acc_txt, ?) "PubMedIDs" from gene_disease_reference gdr inner join term g on gdr.gene_id = g.id inner join term d on gdr.disease_id = d.id left outer join reference r on gdr.reference_id = r.id left outer join term c on gdr.via_chem_id = c.id where (d.id = ?) group by g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end, c.nm, gdr.network_score order by d.nm_sort, g.nm, "DirectEvidence", c.nm;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 18 15 1 5s88ms 5s88ms -
SELECT /* BatchDiseaseGeneAssnsDAO */ 'asthenia' "Input", d.nm "DiseaseName", d.acc_db_cd || ':' || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( SELECT STRING_AGG(stm.slim_term_nm, '|' ORDER BY stm.slim_term_nm) FROM slim_term_mapping stm WHERE stm.mapped_term_id = d.id) "DiseaseCategories", CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", STRING_AGG(gdr.source_acc_txt, '|' ORDER BY gdr.source_acc_txt) "OmimIDs", STRING_AGG(DISTINCT r.acc_txt, '|') "PubMedIDs" FROM gene_disease_reference gdr INNER JOIN term g ON gdr.gene_id = g.id INNER JOIN term d ON gdr.disease_id = d.id LEFT OUTER JOIN reference r ON gdr.reference_id = r.id LEFT OUTER JOIN term c ON gdr.via_chem_id = c.id WHERE (d.id = 2118221) GROUP BY g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END, c.nm, gdr.network_score ORDER BY d.nm_sort, g.nm, "DirectEvidence", c.nm;
Date: 2026-01-18 15:53:33 Duration: 5s88ms Bind query: yes
13 5s5ms 1 5s5ms 5s5ms 5s5ms select ? "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casrn "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" from ( with sq as ( select distinct c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casrn, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort from term c inner join gene_chem_reference gcr on c.id = gcr.chem_id inner join term g on gcr.gene_id = g.id where (c.id = ?)) select distinct sq.chem_nm, sq.chem_acc_txt, sq.casrn, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm from sq inner join gene_go_annot gga on sq.gene_id = gga.gene_id inner join dag_node gt on gga.go_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where gga.is_not = false and (d.id = ? or d.id = ?) order by sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 18 15 1 5s5ms 5s5ms -
SELECT /* BatchChemGODAO */ 'ddt' "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casRN "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" FROM ( WITH sq AS ( SELECT DISTINCT c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casRN, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort FROM term c INNER JOIN gene_chem_reference gcr ON c.id = gcr.chem_id INNER JOIN term g ON gcr.gene_id = g.id WHERE (c.id = 1332236)) SELECT DISTINCT sq.chem_nm, sq.chem_acc_txt, sq.casRN, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm FROM sq INNER JOIN gene_go_annot gga ON sq.gene_id = gga.gene_id INNER JOIN dag_node gt ON gga.go_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE gga.is_not = false AND (d.id = 5 OR d.id = 4) ORDER BY sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;
Date: 2026-01-18 15:53:28 Duration: 5s5ms Bind query: yes
Most frequent queries (N)
Rank Times executed Total duration Min duration Max duration Avg duration Query 1 8 5m2s 6s899ms 1m12s 37s814ms select id, object_type_id, acc_txt, t.acc_db_id, nm, nm_sort, secondary_nm, description, note from load.term t where object_type_id = ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 22 10 2 1m13s 36s592ms 11 2 1m12s 36s223ms 12 4 2m36s 39s220ms [ User: edit - Total duration: 40s994ms - Times executed: 4 ]
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:40:38 Duration: 1m12s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:31:39 Duration: 1m6s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 11:06:47 Duration: 1m1s Bind query: yes
2 4 28s928ms 5s757ms 8s694ms 7s232ms select t.id, t.object_type_id, t.acc_txt, t.acc_db_cd, t.nm, t.nm_sort, t.secondary_nm, t.description, t.note, l.nm from pub2.term t, pub2.term_label l where t.object_type_id = ? and t.id = l.term_id;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jan 18 15 4 28s928ms 7s232ms [ User: editeu - Total duration: 28s928ms - Times executed: 4 ]
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s694ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s327ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 1 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:40 Duration: 6s149ms Database: ctddev51 User: editeu Bind query: yes
3 3 51s262ms 16s651ms 17s837ms 17s87ms select distinct ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm, ( select string_agg(distinct iq.nm, ?)) from edit.ixn i inner join edit.ixn_actor iachem on i.root_id = iachem.ixn_id inner join edit.ixn_actor iadisease on i.root_id = iadisease.ixn_id inner join edit.ixn_action iact on i.root_id = iact.ixn_id inner join edit.action_type at on iact.action_type_id = at.id inner join edit.reference_ixn ri on i.root_id = ri.ixn_id inner join pub2.term chemterm on iachem.acc_txt = chemterm.acc_txt and chemterm.object_type_id = ? inner join pub2.term diseaseterm on iadisease.acc_txt = diseaseterm.acc_txt and diseaseterm.object_type_id = ? left outer join edit.reference_ixn_qualifier riq on ri.id = riq.reference_ixn_id left outer join edit.ixn_qualifier iq on riq.ixn_qualifier_id = iq.id where i.ixn_type_id = ? and iachem.object_type_id = ? and iadisease.object_type_id = ? group by ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 22 11 1 16s773ms 16s773ms 12 2 34s488ms 17s244ms -
select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:31:59 Duration: 17s837ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 11:07:05 Duration: 16s773ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:40:57 Duration: 16s651ms Bind query: yes
4 1 42s420ms 42s420ms 42s420ms 42s420ms select g.nm genesymbol, g.id geneid, g.acc_txt geneacc, g.acc_db_cd geneaccdbcd, c.nm chemnm, c.nm_html chemnmhtml, c.acc_txt chemacc, c.secondary_nm casrn, c.id chemid, i.id ixnid, i.ixn_prose_txt ixnprose, i.ixn_prose_html ixnprosehtml, i.actions_txt ixnactions, count(distinct gcr.reference_id) refcount, count(distinct gcr.taxon_id) taxoncount, count(*) over () fullrowcount from gene_chem_reference gcr inner join ixn i on gcr.ixn_id = i.id inner join term g on gcr.gene_id = g.id inner join term c on gcr.chem_id = c.id where gcr.gene_id = any (array (( select tp.term_id from term_pathway tp where upper(tp.pathway_nm) like ? and tp.object_type_id = ?))) and gcr.id in ( select gcra.gene_chem_reference_id from gene_chem_reference_axn gcra where (gcra.action_degree_type_nm = ?)) group by g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id order by g.nm_sort, c.nm_sort, i.sort_txt limit ?;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 18 15 1 42s420ms 42s420ms -
SELECT /* AdvancedIxnQueryDAO.getData */ g.nm geneSymbol, g.id geneId, g.acc_txt geneAcc, g.acc_db_cd geneAccDbCd, c.nm chemNm, c.nm_html chemNmhtml, c.acc_txt chemAcc, c.secondary_nm casRN, c.id chemId, i.id ixnId, i.ixn_prose_txt ixnProse, i.ixn_prose_html ixnProseHtml, i.actions_txt ixnActions, COUNT(DISTINCT gcr.reference_id) refCount, COUNT(DISTINCT gcr.taxon_id) taxonCount, COUNT(*) OVER () fullRowCount FROM gene_chem_reference gcr INNER JOIN ixn i ON gcr.ixn_id = i.id INNER JOIN term g ON gcr.gene_id = g.id INNER JOIN term c ON gcr.chem_id = c.id WHERE /* CIQH.getIxnWhereCore */ gcr.gene_id = ANY (ARRAY (( SELECT /* IQH.getMasterPathwayWhereEquals.Name */ tp.term_id FROM term_pathway tp WHERE UPPER(tp.pathway_nm) LIKE 'METABOLISM' AND tp.object_type_id = 4))) AND gcr.id IN ( SELECT gcra.gene_chem_reference_id FROM gene_chem_reference_axn gcra WHERE (gcra.action_degree_type_nm = 'increases')) GROUP BY g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id ORDER BY g.nm_sort, c.nm_sort, i.sort_txt LIMIT 50;
Date: 2026-01-18 15:51:30 Duration: 42s420ms Bind query: yes
5 1 37s257ms 37s257ms 37s257ms 37s257ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select ai.gene_id from dag_path pi inner join gene_go_annot ai on pi.descendant_object_id = ai.go_term_id inner join term_label li on li.term_id = pi.ancestor_object_id where upper(li.nm) like ? and li.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 18 15 1 37s257ms 37s257ms -
SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterGoWhereEquals.Gene */ ai.gene_id FROM dag_path pi INNER JOIN gene_go_annot ai ON pi.descendant_object_id = ai.go_term_id INNER JOIN term_label li ON li.term_id = pi.ancestor_object_id WHERE UPPER(li.nm) LIKE 'APOPTOSIS' AND li.object_type_id = 5)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:18 Duration: 37s257ms Bind query: yes
6 1 15s712ms 15s712ms 15s712ms 15s712ms select distinct associatedterm.nm || ? || o.cd || ? || associatedterm.nm_html || ? || associatedterm.acc_txt || ? || associatedterm.acc_db_cd as associatedterm, associatedterm.id associatedtermid, ptr.ixn_id ixnid, associatedterm.object_type_id || ? || associatedterm.nm_sort associatedtermnmsort, coalesce(associatedterm.secondary_nm, ?) casrn, phenotypeterm.nm || ? || ? || ? || phenotypeterm.nm_html || ? || phenotypeterm.acc_txt || ? || phenotypeterm.acc_db_cd as phenotype, phenotypeterm.id phenotypeid, ( select string_agg(distinct taxonterm.nm || ? || ? || ? || taxonterm.nm_html || ? || taxonterm.acc_txt || ? || taxonterm.acc_db_cd || ? || coalesce(taxonterm.secondary_nm, ?), ?)) as taxonterms, ( select string_agg(distinct anatomyterm.nm_html || ? || anatomyterm.acc_txt || ? || ia.level_seq || ? || anatomyterm.acc_db_cd || ? || anatomyterm.nm, ?)) as anatomyterms, count(distinct taxonterm.nm) taxoncount, i.ixn_prose_html ixnprosehtml, i.ixn_prose_txt ixnprose, i.sort_txt ixnsort, ( select string_agg(distinct r.acc_txt, ?)) as references, count(distinct ptr.reference_id) refcount, pt.indirect_term_qty inferredcount, count(*) over () fullrowcount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedterm on ptr.term_id = associatedterm.id inner join term phenotypeterm on ptr.phenotype_id = phenotypeterm.id left outer join term taxonterm on ptr.taxon_id = taxonterm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedterm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyterm on ia.anatomy_id = anatomyterm.id where ptr.term_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?)) and ptr.term_object_type_id = ? and ptr.phenotype_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?))) and taxonterm.id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = ? and action_degree_type_nm in (...)) group by associatedterm, associatedtermnmsort, phenotype, casrn, ixnid, ixnprosehtml, ixnprose, ixnsort, associatedtermid, phenotypeid, inferredcount order by associatedtermnmsort limit ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 18 15 1 15s712ms 15s712ms -
select distinct /* ChemPhenotypesAssnsDAO */ associatedTerm.nm || '^' || o.cd || '^' || associatedTerm.nm_html || '^' || associatedTerm.acc_txt || '^' || associatedTerm.acc_db_cd as associatedTerm, associatedTerm.id associatedTermId, ptr.ixn_id ixnId, associatedTerm.object_type_id || '|' || associatedTerm.nm_sort associatedTermNmSort, COALESCE(associatedTerm.secondary_nm, '') casRN, phenotypeTerm.nm || '^' || 'go' || '^' || phenotypeTerm.nm_html || '^' || phenotypeTerm.acc_txt || '^' || phenotypeTerm.acc_db_cd as phenotype, phenotypeTerm.id phenotypeId, ( SELECT STRING_AGG(distinct taxonTerm.nm || '^' || 'taxon' || '^' || taxonTerm.nm_html || '^' || taxonTerm.acc_txt || '^' || taxonTerm.acc_db_cd || '^' || COALESCE(taxonTerm.secondary_nm, ''), '|')) as taxonTerms, ( SELECT STRING_AGG(distinct anatomyTerm.nm_html || '^' || anatomyTerm.acc_txt || '^' || ia.level_seq || '^' || anatomyTerm.acc_db_cd || '^' || anatomyTerm.nm, '|')) as anatomyTerms, COUNT(DISTINCT taxonTerm.nm) taxonCount, i.ixn_prose_html ixnProseHtml, i.ixn_prose_txt ixnProse, i.sort_txt ixnSort, ( SELECT STRING_AGG(distinct r.acc_txt, '|')) as references, COUNT(DISTINCT ptr.reference_id) refCount, pt.indirect_term_qty inferredCount, COUNT(*) OVER () fullRowCount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedTerm on ptr.term_id = associatedTerm.id inner join term phenotypeTerm on ptr.phenotype_id = phenotypeTerm.id left outer join term taxonTerm on ptr.taxon_id = taxonTerm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedTerm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyTerm on ia.anatomy_id = anatomyTerm.id where ptr.term_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 2 and upper(baseTerm.nm) LIKE 'ACETYLCYSTEINE')) and ptr.term_object_type_id = 2 and ptr.phenotype_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 5 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = 'GO:0006979' AND l.type_cd = 'A' AND l.object_type_id = 5))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 10 and upper(baseTerm.nm) LIKE 'CARDIOVASCULAR SYSTEM'))) and taxonTerm.id in ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 1 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = '9605' AND l.type_cd = 'A' AND l.object_type_id = 1))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = 'phenotype' and action_degree_type_nm in ('increases')) group by associatedTerm, associatedTermNmSort, phenotype, casRN, ixnId, ixnProseHtml, ixnProse, ixnSort, associatedTermId, phenotypeId, inferredCount ORDER BY associatedTermNmSort LIMIT 50;
Date: 2026-01-18 15:54:23 Duration: 15s712ms Bind query: yes
7 1 12s882ms 12s882ms 12s882ms 12s882ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term t inner join dag_path dp on t.id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(t.nm) like ? and t.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jan 18 15 1 12s882ms 12s882ms [ User: pubeu - Total duration: 12s882ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Name.Gene */ gd.gene_id FROM term t INNER JOIN dag_path dp ON t.id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(t.nm) LIKE 'ASTHMA' AND t.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:31 Duration: 12s882ms Database: ctddev51 User: pubeu Bind query: yes
8 1 6s392ms 6s392ms 6s392ms 6s392ms select count(distinct gene_id) from gene_taxon where taxon_id = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 18 15 1 6s392ms 6s392ms [ User: pubeu - Total duration: 6s392ms - Times executed: 1 ]
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select count(distinct gene_id) from GENE_TAXON where taxon_id = 569441;
Date: 2026-01-18 15:19:43 Duration: 6s392ms Database: ctddev51 User: pubeu Bind query: yes
9 1 6s302ms 6s302ms 6s302ms 6s302ms select p.ancestor_object_id, p.descendant_object_id from dag_path p where p.descendant_object_id in ( select go_term_id from gene_go_annot gga where gga.taxon_id = ( select id from term where acc_txt = ? and object_type_id = ( select id from object_type where cd = ?)) and gga.is_not = ?) and p.ancestor_object_id not in ( select c.id from term c where c.acc_txt in (...) and c.object_type_id = ( select id from object_type where cd = ?));Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 18 15 1 6s302ms 6s302ms -
select p.ancestor_object_id, p.descendant_object_id from DAG_PATH p where p.descendant_object_id in ( select go_term_id from GENE_GO_ANNOT gga where gga.taxon_id = ( select id from TERM where acc_txt = '9606' and object_type_id = ( select id from OBJECT_TYPE where cd = 'taxon')) AND gga.is_not = 'f') and p.ancestor_object_id NOT in ( SELECT c.id FROM TERM c WHERE c.acc_txt in ('ALL') AND c.object_type_id = ( select id from OBJECT_TYPE where cd = 'go'));
Date: 2026-01-18 15:19:54 Duration: 6s302ms Bind query: yes
10 1 5s341ms 5s341ms 5s341ms 5s341ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term_label l inner join dag_path dp on l.term_id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(l.nm) like ? and l.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 18 15 1 5s341ms 5s341ms [ User: pubeu - Total duration: 5s341ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Label.Gene */ gd.gene_id FROM term_label l INNER JOIN dag_path dp ON l.term_id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(l.nm) LIKE 'GLAUCOMA' AND l.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:49:41 Duration: 5s341ms Database: ctddev51 User: pubeu Bind query: yes
11 1 5s230ms 5s230ms 5s230ms 5s230ms select d.abbr dagabbr, d.nm dagnm, gt.level_min_no daglevelmin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pvalcorrected, te.raw_p_val pvalraw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, count(*) over () fullrowcount from term_enrichment te inner join dag_node gt on te.enriched_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where te.term_id = ? and te.enriched_object_type_id = ? order by te.corrected_p_val, d.abbr, gt.nm_sort limit ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 21 14 1 5s230ms 5s230ms [ User: pubeu - Total duration: 5s230ms - Times executed: 1 ]
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SELECT /* ChemGODAO */ d.abbr dagAbbr, d.nm dagNm, gt.level_min_no dagLevelMin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pValCorrected, te.raw_p_val pValRaw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, COUNT(*) OVER () fullRowCount FROM term_enrichment te INNER JOIN dag_node gt ON te.enriched_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE te.term_id = '1334144' AND te.enriched_object_type_id = 5 ORDER BY te.corrected_p_val, d.abbr, gt.nm_sort LIMIT 50;
Date: 2026-01-21 14:20:23 Duration: 5s230ms Database: ctddev51 User: pubeu Bind query: yes
12 1 5s88ms 5s88ms 5s88ms 5s88ms select ? "Input", d.nm "DiseaseName", d.acc_db_cd || ? || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( select string_agg(stm.slim_term_nm, ? order by stm.slim_term_nm) from slim_term_mapping stm where stm.mapped_term_id = d.id) "DiseaseCategories", case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", string_agg(gdr.source_acc_txt, ? order by gdr.source_acc_txt) "OmimIDs", string_agg(distinct r.acc_txt, ?) "PubMedIDs" from gene_disease_reference gdr inner join term g on gdr.gene_id = g.id inner join term d on gdr.disease_id = d.id left outer join reference r on gdr.reference_id = r.id left outer join term c on gdr.via_chem_id = c.id where (d.id = ?) group by g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end, c.nm, gdr.network_score order by d.nm_sort, g.nm, "DirectEvidence", c.nm;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 18 15 1 5s88ms 5s88ms -
SELECT /* BatchDiseaseGeneAssnsDAO */ 'asthenia' "Input", d.nm "DiseaseName", d.acc_db_cd || ':' || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( SELECT STRING_AGG(stm.slim_term_nm, '|' ORDER BY stm.slim_term_nm) FROM slim_term_mapping stm WHERE stm.mapped_term_id = d.id) "DiseaseCategories", CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", STRING_AGG(gdr.source_acc_txt, '|' ORDER BY gdr.source_acc_txt) "OmimIDs", STRING_AGG(DISTINCT r.acc_txt, '|') "PubMedIDs" FROM gene_disease_reference gdr INNER JOIN term g ON gdr.gene_id = g.id INNER JOIN term d ON gdr.disease_id = d.id LEFT OUTER JOIN reference r ON gdr.reference_id = r.id LEFT OUTER JOIN term c ON gdr.via_chem_id = c.id WHERE (d.id = 2118221) GROUP BY g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END, c.nm, gdr.network_score ORDER BY d.nm_sort, g.nm, "DirectEvidence", c.nm;
Date: 2026-01-18 15:53:33 Duration: 5s88ms Bind query: yes
13 1 5s5ms 5s5ms 5s5ms 5s5ms select ? "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casrn "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" from ( with sq as ( select distinct c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casrn, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort from term c inner join gene_chem_reference gcr on c.id = gcr.chem_id inner join term g on gcr.gene_id = g.id where (c.id = ?)) select distinct sq.chem_nm, sq.chem_acc_txt, sq.casrn, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm from sq inner join gene_go_annot gga on sq.gene_id = gga.gene_id inner join dag_node gt on gga.go_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where gga.is_not = false and (d.id = ? or d.id = ?) order by sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 18 15 1 5s5ms 5s5ms -
SELECT /* BatchChemGODAO */ 'ddt' "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casRN "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" FROM ( WITH sq AS ( SELECT DISTINCT c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casRN, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort FROM term c INNER JOIN gene_chem_reference gcr ON c.id = gcr.chem_id INNER JOIN term g ON gcr.gene_id = g.id WHERE (c.id = 1332236)) SELECT DISTINCT sq.chem_nm, sq.chem_acc_txt, sq.casRN, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm FROM sq INNER JOIN gene_go_annot gga ON sq.gene_id = gga.gene_id INNER JOIN dag_node gt ON gga.go_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE gga.is_not = false AND (d.id = 5 OR d.id = 4) ORDER BY sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;
Date: 2026-01-18 15:53:28 Duration: 5s5ms Bind query: yes
Normalized slowest queries (N)
Rank Min duration Max duration Avg duration Times executed Total duration Query 1 42s420ms 42s420ms 42s420ms 1 42s420ms select g.nm genesymbol, g.id geneid, g.acc_txt geneacc, g.acc_db_cd geneaccdbcd, c.nm chemnm, c.nm_html chemnmhtml, c.acc_txt chemacc, c.secondary_nm casrn, c.id chemid, i.id ixnid, i.ixn_prose_txt ixnprose, i.ixn_prose_html ixnprosehtml, i.actions_txt ixnactions, count(distinct gcr.reference_id) refcount, count(distinct gcr.taxon_id) taxoncount, count(*) over () fullrowcount from gene_chem_reference gcr inner join ixn i on gcr.ixn_id = i.id inner join term g on gcr.gene_id = g.id inner join term c on gcr.chem_id = c.id where gcr.gene_id = any (array (( select tp.term_id from term_pathway tp where upper(tp.pathway_nm) like ? and tp.object_type_id = ?))) and gcr.id in ( select gcra.gene_chem_reference_id from gene_chem_reference_axn gcra where (gcra.action_degree_type_nm = ?)) group by g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id order by g.nm_sort, c.nm_sort, i.sort_txt limit ?;Times Reported Time consuming queries #1
Day Hour Count Duration Avg duration Jan 18 15 1 42s420ms 42s420ms -
SELECT /* AdvancedIxnQueryDAO.getData */ g.nm geneSymbol, g.id geneId, g.acc_txt geneAcc, g.acc_db_cd geneAccDbCd, c.nm chemNm, c.nm_html chemNmhtml, c.acc_txt chemAcc, c.secondary_nm casRN, c.id chemId, i.id ixnId, i.ixn_prose_txt ixnProse, i.ixn_prose_html ixnProseHtml, i.actions_txt ixnActions, COUNT(DISTINCT gcr.reference_id) refCount, COUNT(DISTINCT gcr.taxon_id) taxonCount, COUNT(*) OVER () fullRowCount FROM gene_chem_reference gcr INNER JOIN ixn i ON gcr.ixn_id = i.id INNER JOIN term g ON gcr.gene_id = g.id INNER JOIN term c ON gcr.chem_id = c.id WHERE /* CIQH.getIxnWhereCore */ gcr.gene_id = ANY (ARRAY (( SELECT /* IQH.getMasterPathwayWhereEquals.Name */ tp.term_id FROM term_pathway tp WHERE UPPER(tp.pathway_nm) LIKE 'METABOLISM' AND tp.object_type_id = 4))) AND gcr.id IN ( SELECT gcra.gene_chem_reference_id FROM gene_chem_reference_axn gcra WHERE (gcra.action_degree_type_nm = 'increases')) GROUP BY g.nm, g.nm_sort, g.acc_txt, g.acc_db_cd, g.id, c.nm, c.nm_html, c.nm_sort, c.acc_txt, c.secondary_nm, c.id, i.ixn_prose_txt, i.ixn_prose_html, i.sort_txt, i.actions_txt, i.id ORDER BY g.nm_sort, c.nm_sort, i.sort_txt LIMIT 50;
Date: 2026-01-18 15:51:30 Duration: 42s420ms Bind query: yes
2 6s899ms 1m12s 37s814ms 8 5m2s select id, object_type_id, acc_txt, t.acc_db_id, nm, nm_sort, secondary_nm, description, note from load.term t where object_type_id = ?;Times Reported Time consuming queries #2
Day Hour Count Duration Avg duration Jan 22 10 2 1m13s 36s592ms 11 2 1m12s 36s223ms 12 4 2m36s 39s220ms [ User: edit - Total duration: 40s994ms - Times executed: 4 ]
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:40:38 Duration: 1m12s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 12:31:39 Duration: 1m6s Bind query: yes
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select ID, OBJECT_TYPE_ID, ACC_TXT, t.ACC_DB_ID, NM, NM_SORT, SECONDARY_NM, DESCRIPTION, NOTE from load.term t where object_type_id = 1;
Date: 2026-01-22 11:06:47 Duration: 1m1s Bind query: yes
3 37s257ms 37s257ms 37s257ms 1 37s257ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select ai.gene_id from dag_path pi inner join gene_go_annot ai on pi.descendant_object_id = ai.go_term_id inner join term_label li on li.term_id = pi.ancestor_object_id where upper(li.nm) like ? and li.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #3
Day Hour Count Duration Avg duration Jan 18 15 1 37s257ms 37s257ms -
SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterGoWhereEquals.Gene */ ai.gene_id FROM dag_path pi INNER JOIN gene_go_annot ai ON pi.descendant_object_id = ai.go_term_id INNER JOIN term_label li ON li.term_id = pi.ancestor_object_id WHERE UPPER(li.nm) LIKE 'APOPTOSIS' AND li.object_type_id = 5)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:18 Duration: 37s257ms Bind query: yes
4 16s651ms 17s837ms 17s87ms 3 51s262ms select distinct ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm, ( select string_agg(distinct iq.nm, ?)) from edit.ixn i inner join edit.ixn_actor iachem on i.root_id = iachem.ixn_id inner join edit.ixn_actor iadisease on i.root_id = iadisease.ixn_id inner join edit.ixn_action iact on i.root_id = iact.ixn_id inner join edit.action_type at on iact.action_type_id = at.id inner join edit.reference_ixn ri on i.root_id = ri.ixn_id inner join pub2.term chemterm on iachem.acc_txt = chemterm.acc_txt and chemterm.object_type_id = ? inner join pub2.term diseaseterm on iadisease.acc_txt = diseaseterm.acc_txt and diseaseterm.object_type_id = ? left outer join edit.reference_ixn_qualifier riq on ri.id = riq.reference_ixn_id left outer join edit.ixn_qualifier iq on riq.ixn_qualifier_id = iq.id where i.ixn_type_id = ? and iachem.object_type_id = ? and iadisease.object_type_id = ? group by ri.reference_acc_txt, iachem.acc_txt, at.cd, iadisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemterm.nm, diseaseterm.nm;Times Reported Time consuming queries #4
Day Hour Count Duration Avg duration Jan 22 11 1 16s773ms 16s773ms 12 2 34s488ms 17s244ms -
select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:31:59 Duration: 17s837ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 11:07:05 Duration: 16s773ms Bind query: yes
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select DISTINCT ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm, ( SELECT STRING_AGG(DISTINCT iq.nm, '|')) from edit.IXN i INNER JOIN edit.IXN_ACTOR iaChem ON i.root_id = iaChem.ixn_id INNER JOIN edit.IXN_ACTOR iaDisease ON i.root_id = iaDisease.ixn_id INNER JOIN edit.IXN_ACTION iAct ON i.root_id = iAct.ixn_id INNER JOIN edit.ACTION_TYPE at ON iAct.action_type_id = at.id INNER JOIN edit.REFERENCE_IXN ri ON i.root_id = ri.ixn_id INNER JOIN pub2.TERM chemTerm ON iaChem.acc_txt = chemTerm.acc_txt and chemTerm.object_type_id = 2 INNER JOIN pub2.TERM diseaseTerm ON iaDisease.acc_txt = diseaseTerm.acc_txt and diseaseTerm.object_type_id = 3 LEFT OUTER JOIN edit.REFERENCE_IXN_QUALIFIER riq ON ri.id = riq.reference_ixn_id LEFT OUTER JOIN edit.IXN_QUALIFIER iq ON riq.ixn_qualifier_id = iq.id where i.ixn_type_id = 2 and iaChem.object_type_id = 2 and iaDisease.object_type_id = 3 group by ri.reference_acc_txt, iaChem.acc_txt, at.cd, iaDisease.acc_txt, ri.taxon_acc_txt, i.root_id, chemTerm.nm, diseaseTerm.nm;
Date: 2026-01-22 12:40:57 Duration: 16s651ms Bind query: yes
5 15s712ms 15s712ms 15s712ms 1 15s712ms select distinct associatedterm.nm || ? || o.cd || ? || associatedterm.nm_html || ? || associatedterm.acc_txt || ? || associatedterm.acc_db_cd as associatedterm, associatedterm.id associatedtermid, ptr.ixn_id ixnid, associatedterm.object_type_id || ? || associatedterm.nm_sort associatedtermnmsort, coalesce(associatedterm.secondary_nm, ?) casrn, phenotypeterm.nm || ? || ? || ? || phenotypeterm.nm_html || ? || phenotypeterm.acc_txt || ? || phenotypeterm.acc_db_cd as phenotype, phenotypeterm.id phenotypeid, ( select string_agg(distinct taxonterm.nm || ? || ? || ? || taxonterm.nm_html || ? || taxonterm.acc_txt || ? || taxonterm.acc_db_cd || ? || coalesce(taxonterm.secondary_nm, ?), ?)) as taxonterms, ( select string_agg(distinct anatomyterm.nm_html || ? || anatomyterm.acc_txt || ? || ia.level_seq || ? || anatomyterm.acc_db_cd || ? || anatomyterm.nm, ?)) as anatomyterms, count(distinct taxonterm.nm) taxoncount, i.ixn_prose_html ixnprosehtml, i.ixn_prose_txt ixnprose, i.sort_txt ixnsort, ( select string_agg(distinct r.acc_txt, ?)) as references, count(distinct ptr.reference_id) refcount, pt.indirect_term_qty inferredcount, count(*) over () fullrowcount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedterm on ptr.term_id = associatedterm.id inner join term phenotypeterm on ptr.phenotype_id = phenotypeterm.id left outer join term taxonterm on ptr.taxon_id = taxonterm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedterm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyterm on ia.anatomy_id = anatomyterm.id where ptr.term_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?)) and ptr.term_object_type_id = ? and ptr.phenotype_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and upper(baseterm.nm) like ?))) and taxonterm.id in ( select distinct dp.descendant_object_id from dag_path dp where dp.ancestor_object_id in ( select distinct id from term baseterm where object_type_id = ? and baseterm.id in ( select object_id from db_link l where l.acc_txt = ? and l.type_cd = ? and l.object_type_id = ?))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = ? and action_degree_type_nm in (...)) group by associatedterm, associatedtermnmsort, phenotype, casrn, ixnid, ixnprosehtml, ixnprose, ixnsort, associatedtermid, phenotypeid, inferredcount order by associatedtermnmsort limit ?;Times Reported Time consuming queries #5
Day Hour Count Duration Avg duration Jan 18 15 1 15s712ms 15s712ms -
select distinct /* ChemPhenotypesAssnsDAO */ associatedTerm.nm || '^' || o.cd || '^' || associatedTerm.nm_html || '^' || associatedTerm.acc_txt || '^' || associatedTerm.acc_db_cd as associatedTerm, associatedTerm.id associatedTermId, ptr.ixn_id ixnId, associatedTerm.object_type_id || '|' || associatedTerm.nm_sort associatedTermNmSort, COALESCE(associatedTerm.secondary_nm, '') casRN, phenotypeTerm.nm || '^' || 'go' || '^' || phenotypeTerm.nm_html || '^' || phenotypeTerm.acc_txt || '^' || phenotypeTerm.acc_db_cd as phenotype, phenotypeTerm.id phenotypeId, ( SELECT STRING_AGG(distinct taxonTerm.nm || '^' || 'taxon' || '^' || taxonTerm.nm_html || '^' || taxonTerm.acc_txt || '^' || taxonTerm.acc_db_cd || '^' || COALESCE(taxonTerm.secondary_nm, ''), '|')) as taxonTerms, ( SELECT STRING_AGG(distinct anatomyTerm.nm_html || '^' || anatomyTerm.acc_txt || '^' || ia.level_seq || '^' || anatomyTerm.acc_db_cd || '^' || anatomyTerm.nm, '|')) as anatomyTerms, COUNT(DISTINCT taxonTerm.nm) taxonCount, i.ixn_prose_html ixnProseHtml, i.ixn_prose_txt ixnProse, i.sort_txt ixnSort, ( SELECT STRING_AGG(distinct r.acc_txt, '|')) as references, COUNT(DISTINCT ptr.reference_id) refCount, pt.indirect_term_qty inferredCount, COUNT(*) OVER () fullRowCount from phenotype_term_reference ptr inner join phenotype_term pt on ptr.term_id = pt.term_id and ptr.phenotype_id = pt.phenotype_id inner join term associatedTerm on ptr.term_id = associatedTerm.id inner join term phenotypeTerm on ptr.phenotype_id = phenotypeTerm.id left outer join term taxonTerm on ptr.taxon_id = taxonTerm.id inner join reference r on ptr.reference_id = r.id inner join ixn i on ptr.ixn_id = i.id inner join object_type o on associatedTerm.object_type_id = o.id left outer join ixn_anatomy ia on ptr.ixn_id = ia.ixn_id left outer join term anatomyTerm on ia.anatomy_id = anatomyTerm.id where ptr.term_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 2 and upper(baseTerm.nm) LIKE 'ACETYLCYSTEINE')) and ptr.term_object_type_id = 2 and ptr.phenotype_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 5 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = 'GO:0006979' AND l.type_cd = 'A' AND l.object_type_id = 5))) and i.id in ( select ixn_id from ixn_anatomy where anatomy_id IN ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 10 and upper(baseTerm.nm) LIKE 'CARDIOVASCULAR SYSTEM'))) and taxonTerm.id in ( select /* DBConstants.getDAGTermSQL */ distinct dp.descendant_object_id from dag_path dp WHERE dp.ancestor_object_id in ( select distinct id from term baseTerm where object_type_id = 1 and baseTerm.id in ( select object_id from db_link l where l.acc_txt = '9605' AND l.type_cd = 'A' AND l.object_type_id = 1))) and i.id in ( select ixn_id from ixn_axn where action_type_nm = 'phenotype' and action_degree_type_nm in ('increases')) group by associatedTerm, associatedTermNmSort, phenotype, casRN, ixnId, ixnProseHtml, ixnProse, ixnSort, associatedTermId, phenotypeId, inferredCount ORDER BY associatedTermNmSort LIMIT 50;
Date: 2026-01-18 15:54:23 Duration: 15s712ms Bind query: yes
6 12s882ms 12s882ms 12s882ms 1 12s882ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term t inner join dag_path dp on t.id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(t.nm) like ? and t.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #6
Day Hour Count Duration Avg duration Jan 18 15 1 12s882ms 12s882ms [ User: pubeu - Total duration: 12s882ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Name.Gene */ gd.gene_id FROM term t INNER JOIN dag_path dp ON t.id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(t.nm) LIKE 'ASTHMA' AND t.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:50:31 Duration: 12s882ms Database: ctddev51 User: pubeu Bind query: yes
7 5s757ms 8s694ms 7s232ms 4 28s928ms select t.id, t.object_type_id, t.acc_txt, t.acc_db_cd, t.nm, t.nm_sort, t.secondary_nm, t.description, t.note, l.nm from pub2.term t, pub2.term_label l where t.object_type_id = ? and t.id = l.term_id;Times Reported Time consuming queries #7
Day Hour Count Duration Avg duration Jan 18 15 4 28s928ms 7s232ms [ User: editeu - Total duration: 28s928ms - Times executed: 4 ]
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s694ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 4 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:42 Duration: 8s327ms Database: ctddev51 User: editeu Bind query: yes
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select t.ID, t.OBJECT_TYPE_ID, t.ACC_TXT, t.ACC_DB_CD, t.NM, t.NM_SORT, t.SECONDARY_NM, t.DESCRIPTION, t.NOTE, l.NM from pub2.TERM t, pub2.TERM_LABEL l where t.OBJECT_TYPE_ID = 1 and t.id = l.TERM_ID;
Date: 2026-01-18 15:19:40 Duration: 6s149ms Database: ctddev51 User: editeu Bind query: yes
8 6s392ms 6s392ms 6s392ms 1 6s392ms select count(distinct gene_id) from gene_taxon where taxon_id = ?;Times Reported Time consuming queries #8
Day Hour Count Duration Avg duration Jan 18 15 1 6s392ms 6s392ms [ User: pubeu - Total duration: 6s392ms - Times executed: 1 ]
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select count(distinct gene_id) from GENE_TAXON where taxon_id = 569441;
Date: 2026-01-18 15:19:43 Duration: 6s392ms Database: ctddev51 User: pubeu Bind query: yes
9 6s302ms 6s302ms 6s302ms 1 6s302ms select p.ancestor_object_id, p.descendant_object_id from dag_path p where p.descendant_object_id in ( select go_term_id from gene_go_annot gga where gga.taxon_id = ( select id from term where acc_txt = ? and object_type_id = ( select id from object_type where cd = ?)) and gga.is_not = ?) and p.ancestor_object_id not in ( select c.id from term c where c.acc_txt in (...) and c.object_type_id = ( select id from object_type where cd = ?));Times Reported Time consuming queries #9
Day Hour Count Duration Avg duration Jan 18 15 1 6s302ms 6s302ms -
select p.ancestor_object_id, p.descendant_object_id from DAG_PATH p where p.descendant_object_id in ( select go_term_id from GENE_GO_ANNOT gga where gga.taxon_id = ( select id from TERM where acc_txt = '9606' and object_type_id = ( select id from OBJECT_TYPE where cd = 'taxon')) AND gga.is_not = 'f') and p.ancestor_object_id NOT in ( SELECT c.id FROM TERM c WHERE c.acc_txt in ('ALL') AND c.object_type_id = ( select id from OBJECT_TYPE where cd = 'go'));
Date: 2026-01-18 15:19:54 Duration: 6s302ms Bind query: yes
10 5s341ms 5s341ms 5s341ms 1 5s341ms select g.id geneid, g.acc_txt acc, g.nm nm, g.nm nmhtml, g.secondary_nm secondarynm, g.has_chems haschems, g.has_diseases hasdiseases, g.has_exposures hasexposures, g.has_phenotypes hasphenotypes, count(*) over () fullrowcount from term g where g.id in (( select gd.gene_id from term_label l inner join dag_path dp on l.term_id = dp.ancestor_object_id inner join gene_disease gd on dp.descendant_object_id = gd.disease_id where upper(l.nm) like ? and l.object_type_id = ?)) order by g.nm_sort, g.id limit ?;Times Reported Time consuming queries #10
Day Hour Count Duration Avg duration Jan 18 15 1 5s341ms 5s341ms [ User: pubeu - Total duration: 5s341ms - Times executed: 1 ]
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SELECT /* AdvancedGeneQueryDAO.getData */ g.id geneId, g.acc_txt acc, g.nm nm, g.nm nmHtml, g.secondary_nm secondaryNm, g.has_chems hasChems, g.has_diseases hasDiseases, g.has_exposures hasExposures, g.has_phenotypes hasPhenotypes, COUNT(*) OVER () fullRowCount FROM term g WHERE g.id IN (( SELECT /* IQH.getMasterDiseaseWhereEquals.Label.Gene */ gd.gene_id FROM term_label l INNER JOIN dag_path dp ON l.term_id = dp.ancestor_object_id INNER JOIN gene_disease gd ON dp.descendant_object_id = gd.disease_id WHERE UPPER(l.nm) LIKE 'GLAUCOMA' AND l.object_type_id = 3)) ORDER BY g.nm_sort, g.id LIMIT 50;
Date: 2026-01-18 15:49:41 Duration: 5s341ms Database: ctddev51 User: pubeu Bind query: yes
11 5s230ms 5s230ms 5s230ms 1 5s230ms select d.abbr dagabbr, d.nm dagnm, gt.level_min_no daglevelmin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pvalcorrected, te.raw_p_val pvalraw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, count(*) over () fullrowcount from term_enrichment te inner join dag_node gt on te.enriched_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where te.term_id = ? and te.enriched_object_type_id = ? order by te.corrected_p_val, d.abbr, gt.nm_sort limit ?;Times Reported Time consuming queries #11
Day Hour Count Duration Avg duration Jan 21 14 1 5s230ms 5s230ms [ User: pubeu - Total duration: 5s230ms - Times executed: 1 ]
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SELECT /* ChemGODAO */ d.abbr dagAbbr, d.nm dagNm, gt.level_min_no dagLevelMin, gt.nm gonm, gt.nm_html gonmhtml, gt.acc_txt goacc, gt.object_id goid, te.corrected_p_val pValCorrected, te.raw_p_val pValRaw, te.target_match_qty targetmatchqty, te.target_total_qty targettotalqty, te.background_match_qty backgroundmatchqty, te.background_total_qty backgroundtotalqty, COUNT(*) OVER () fullRowCount FROM term_enrichment te INNER JOIN dag_node gt ON te.enriched_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE te.term_id = '1334144' AND te.enriched_object_type_id = 5 ORDER BY te.corrected_p_val, d.abbr, gt.nm_sort LIMIT 50;
Date: 2026-01-21 14:20:23 Duration: 5s230ms Database: ctddev51 User: pubeu Bind query: yes
12 5s88ms 5s88ms 5s88ms 1 5s88ms select ? "Input", d.nm "DiseaseName", d.acc_db_cd || ? || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( select string_agg(stm.slim_term_nm, ? order by stm.slim_term_nm) from slim_term_mapping stm where stm.mapped_term_id = d.id) "DiseaseCategories", case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", string_agg(gdr.source_acc_txt, ? order by gdr.source_acc_txt) "OmimIDs", string_agg(distinct r.acc_txt, ?) "PubMedIDs" from gene_disease_reference gdr inner join term g on gdr.gene_id = g.id inner join term d on gdr.disease_id = d.id left outer join reference r on gdr.reference_id = r.id left outer join term c on gdr.via_chem_id = c.id where (d.id = ?) group by g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, case when gdr.via_chem_id is null then ( select string_agg(a.action_type_nm, ?) from gene_disease_axn a where a.gene_id = gdr.gene_id and a.disease_id = gdr.disease_id) else null end, c.nm, gdr.network_score order by d.nm_sort, g.nm, "DirectEvidence", c.nm;Times Reported Time consuming queries #12
Day Hour Count Duration Avg duration Jan 18 15 1 5s88ms 5s88ms -
SELECT /* BatchDiseaseGeneAssnsDAO */ 'asthenia' "Input", d.nm "DiseaseName", d.acc_db_cd || ':' || d.acc_txt "DiseaseID", g.nm "GeneSymbol", g.acc_txt "GeneID", ( SELECT STRING_AGG(stm.slim_term_nm, '|' ORDER BY stm.slim_term_nm) FROM slim_term_mapping stm WHERE stm.mapped_term_id = d.id) "DiseaseCategories", CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END "DirectEvidence", c.nm "InferenceChemicalName", gdr.network_score "InferenceScore", STRING_AGG(gdr.source_acc_txt, '|' ORDER BY gdr.source_acc_txt) "OmimIDs", STRING_AGG(DISTINCT r.acc_txt, '|') "PubMedIDs" FROM gene_disease_reference gdr INNER JOIN term g ON gdr.gene_id = g.id INNER JOIN term d ON gdr.disease_id = d.id LEFT OUTER JOIN reference r ON gdr.reference_id = r.id LEFT OUTER JOIN term c ON gdr.via_chem_id = c.id WHERE (d.id = 2118221) GROUP BY g.nm, g.acc_txt, d.nm, d.id, d.acc_txt, d.acc_db_cd, d.nm_sort, CASE WHEN gdr.via_chem_id IS NULL THEN ( SELECT STRING_AGG(a.action_type_nm, '|') FROM gene_disease_axn a WHERE a.gene_id = gdr.gene_id AND a.disease_id = gdr.disease_id) ELSE NULL END, c.nm, gdr.network_score ORDER BY d.nm_sort, g.nm, "DirectEvidence", c.nm;
Date: 2026-01-18 15:53:33 Duration: 5s88ms Bind query: yes
13 5s5ms 5s5ms 5s5ms 1 5s5ms select ? "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casrn "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" from ( with sq as ( select distinct c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casrn, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort from term c inner join gene_chem_reference gcr on c.id = gcr.chem_id inner join term g on gcr.gene_id = g.id where (c.id = ?)) select distinct sq.chem_nm, sq.chem_acc_txt, sq.casrn, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm from sq inner join gene_go_annot gga on sq.gene_id = gga.gene_id inner join dag_node gt on gga.go_term_id = gt.object_id inner join dag d on gt.dag_id = d.id where gga.is_not = false and (d.id = ? or d.id = ?) order by sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;Times Reported Time consuming queries #13
Day Hour Count Duration Avg duration Jan 18 15 1 5s5ms 5s5ms -
SELECT /* BatchChemGODAO */ 'ddt' "Input", sqi.chem_nm "ChemicalName", sqi.chem_acc_txt "ChemicalID", sqi.casRN "CasRN", sqi.gene_symbol "GeneSymbol", sqi.gene_acc_txt "GeneID", sqi.ontology_nm "Ontology", sqi.go_term_nm "GoTermName", sqi.go_acc_txt "GoTermID" FROM ( WITH sq AS ( SELECT DISTINCT c.id chem_id, c.nm chem_nm, c.acc_txt chem_acc_txt, c.secondary_nm casRN, c.nm_sort chem_nm_sort, gcr.gene_id, g.nm gene_symbol, g.acc_txt gene_acc_txt, g.nm_sort gene_symbol_sort FROM term c INNER JOIN gene_chem_reference gcr ON c.id = gcr.chem_id INNER JOIN term g ON gcr.gene_id = g.id WHERE (c.id = 1332236)) SELECT DISTINCT sq.chem_nm, sq.chem_acc_txt, sq.casRN, sq.gene_symbol, sq.gene_acc_txt, gt.nm go_term_nm, gt.acc_txt go_acc_txt, sq.chem_nm_sort, sq.gene_symbol_sort, gt.nm_sort, d.nm ontology_nm FROM sq INNER JOIN gene_go_annot gga ON sq.gene_id = gga.gene_id INNER JOIN dag_node gt ON gga.go_term_id = gt.object_id INNER JOIN dag d ON gt.dag_id = d.id WHERE gga.is_not = false AND (d.id = 5 OR d.id = 4) ORDER BY sq.chem_nm_sort, sq.gene_symbol_sort, d.nm, gt.nm_sort) sqi;
Date: 2026-01-18 15:53:28 Duration: 5s5ms Bind query: yes
Time consuming prepare
Rank Total duration Times executed Min duration Max duration Avg duration Query NO DATASET
Time consuming bind
Rank Total duration Times executed Min duration Max duration Avg duration Query NO DATASET
-
Events
Log levels
Key values
- 2,811 Event entries
- (EVENTLOG entries are formaly LOG level entries that are not queries)
Events distribution (except queries)
Key values
- 0 PANIC entries
- 0 FATAL entries
- 51 ERROR entries
- 1 WARNING entries
- 37 EVENTLOG entries
Most Frequent Errors/Events
Key values
- 22 Max number of times the same event was reported
- 89 Total events found
Rank Times reported Error 1 22 LOG: could not receive data from client: Connection timed out
Times Reported Most Frequent Error / Event #1
Day Hour Count Jan 18 09 1 11 3 Jan 20 18 1 19 1 Jan 21 17 1 18 1 19 2 Jan 22 18 1 19 2 Jan 23 17 1 18 8 2 14 LOG: could not receive data from client: Connection reset by peer
Times Reported Most Frequent Error / Event #2
Day Hour Count Jan 20 10 2 Jan 22 10 1 11 1 12 2 Jan 23 13 8 3 13 ERROR: relation "..." does not exist
Times Reported Most Frequent Error / Event #3
Day Hour Count Jan 20 10 1 15 7 16 3 Jan 21 16 1 Jan 22 11 1 - ERROR: relation "chem_conc_anatomy" does not exist at character 15
- ERROR: relation "chem_conc_exp_route" does not exist at character 15
- ERROR: relation "action_type" does not exist at character 15
Statement: select * from chem_conc_anatomy
Date: 2026-01-20 10:15:55 Database: ctddev51 Application: pgAdmin 4 - CONN:3414880 User: load Remote:
Statement: select * from chem_conc_exp_route
Date: 2026-01-20 15:12:34
Statement: select * from action_type
Date: 2026-01-20 15:24:45
4 10 ERROR: column "..." does not exist
Times Reported Most Frequent Error / Event #4
Day Hour Count Jan 20 10 1 15 1 16 3 Jan 21 10 1 15 1 Jan 22 10 1 15 2 - ERROR: column "id" does not exist at character 12
- ERROR: column chemconcexproute.exp_route does not exist at character 1145
- ERROR: column at.ixn_id does not exist at character 168
Statement: select max(id) from chem_conc_anatomy
Date: 2026-01-20 10:53:35 Database: ctddev51 Application: pgAdmin 4 - CONN:2916556 User: load Remote:
Statement: ------------------------------------------------------ SELECT cc.id -- id ,cc.reference_acc_txt -- reference_acc_txt ,cc.reference_acc_db_id -- reference_acc_db_id ,cc.chem_acc_txt -- chem_acc_txt ,cc.chem_acc_db_id -- chem_acc_db_id ,chemTerm.nm -- chem_nm ,chemTerm.nm_html -- chem_nm_html ,cc.chem_conc -- chem_conc ,cc.chem_conc_range -- chem_conc_range ,cc.taxon_acc_txt -- taxon_acc_txt ,cc.taxon_acc_db_id -- taxon_acc_db_id ,taxonTerm.nm -- taxon_nm ,taxonTerm.nm_html -- taxon_nm_html -- ,cc.disease_acc_txt -- disease_acc_txt -- ,cc.disease_acc_db_id -- disease_acc_db_id -- ,diseaseTerm.nm -- disease_nm -- ,diseaseTerm.nm_html -- disease_nm_html ,chemConcExpRoute.exp_route -- chem_conc_exp_route_nm -- ,ixnQualifier.nm -- ixn_qualifier_nm ,cc.note -- note -- ,actionType.cd -- action_type_cd ,cc.chem_co_nm -- chem_co_nm ,cc.chem_catalog_nbr -- chem_catalog_nbr ------------------------------------------------------ FROM load.chem_conc cc INNER JOIN pub1.term chemTerm ON cc.chem_acc_txt = chemTerm.acc_txt AND -- cc.chem_acc_db_id = chemTerm.acc_db_id AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) INNER JOIN pub1.term taxonTerm ON cc.taxon_acc_txt = taxonTerm.acc_txt AND -- cc.taxon_acc_db_id = taxonTerm.acc_db_id AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) left OUTER JOIN edit.chem_conc_exp_route chemConcExpRoute ON cc.chem_conc_exp_route_id = chemConcExpRoute.id -- INNER JOIN edit.ixn_qualifier ixnQualifier ON cc.chem_conc_exp_route_id = chemConcExpRoute.id -- INNER JOIN edit.action_type actionType -- INNER JOIN ixn_qualifier ixnQualifier ON cc.ixn_qualifier_id = ixnQualifier.id -- left_outer join ixn i ON cc.ixn_id = i.id ON cc.ixn_qualifier_id = ixnQualifier.id -- INNER JOIN pub1.term diseaseTerm -- ,ixn_actor ia ------------------------------------------------------ -- WHERE cc.chem_acc_txt = chemTerm.acc_txt -- AND cc.chem_acc_db_id = chemTerm.acc_db_id -- AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) -- ------------------------------------------------------ -- AND cc.taxon_acc_txt = taxonTerm.acc_txt -- AND cc.taxon_acc_db_id = taxonTerm.acc_db_id -- AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) ------------------------------------------------------ --AND cc.disease_acc_txt = diseaseTerm.acc_txt --AND cc.disease_acc_db_id = diseaseTerm.acc_db_id --AND diseaseTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'disease' ) ------------------------------------------------------ --AND cc.chem_conc_exp_route_id = chemConcExpRoute.id ------------------------------------------------------ --AND cc.ixn_qualifier_id = ixnQualifier.id ------------------------------------------------------ limit 100
Date: 2026-01-20 15:14:04
Hint: Perhaps you meant to reference the column "ia.ixn_id".
Statement: select ia.ixn_id ,at.cd -- ,atd.cd from edit.ixn_action ia ,edit.action_type at --,edit.action_type_degree atd where ia.ixn_id = 8382512 and ia.ixn_id = at.ixn_id and ia.action_type_id = at.id -- and ia.action_degree_type_id = atd.id limit 100Date: 2026-01-20 16:02:20
5 8 ERROR: syntax error at or near "..."
Times Reported Most Frequent Error / Event #5
Day Hour Count Jan 20 15 1 16 1 Jan 21 10 1 14 1 16 3 Jan 23 09 1 - ERROR: syntax error at or near "select" at character 3856
- ERROR: syntax error at or near "left_outer" at character 2304
- ERROR: syntax error at or near ".." at character 28
Statement: ------------------------------------------------------ SELECT cc.id -- id ,cc.reference_acc_txt -- reference_acc_txt ,cc.reference_acc_db_id -- reference_acc_db_id ,cc.chem_acc_txt -- chem_acc_txt ,cc.chem_acc_db_id -- chem_acc_db_id ,chemTerm.nm -- chem_nm ,chemTerm.nm_html -- chem_nm_html ,cc.chem_conc -- chem_conc ,cc.chem_conc_range -- chem_conc_range ,cc.taxon_acc_txt -- taxon_acc_txt ,cc.taxon_acc_db_id -- taxon_acc_db_id ,taxonTerm.nm -- taxon_nm ,taxonTerm.nm_html -- taxon_nm_html -- ,cc.disease_acc_txt -- disease_acc_txt -- ,cc.disease_acc_db_id -- disease_acc_db_id -- ,diseaseTerm.nm -- disease_nm -- ,diseaseTerm.nm_html -- disease_nm_html -- ,chemConcExpRoute.exp_route -- chem_conc_exp_route_nm -- ,ixnQualifier.nm -- ixn_qualifier_nm ,cc.note -- note -- ,actionType.cd -- action_type_cd ,cc.chem_co_nm -- chem_co_nm ,cc.chem_catalog_nbr -- chem_catalog_nbr ------------------------------------------------------ FROM load.chem_conc cc INNER JOIN pub1.term chemTerm ON cc.chem_acc_txt = chemTerm.acc_txt AND -- cc.chem_acc_db_id = chemTerm.acc_db_id AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) INNER JOIN pub1.term taxonTerm ON cc.taxon_acc_txt = taxonTerm.acc_txt AND -- cc.taxon_acc_db_id = taxonTerm.acc_db_id AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) left OUTER JOIN edit.chem_conc_exp_route chemConcExpRoute ON cc.chem_conc_exp_route_id = chemConcExpRoute.id -- INNER JOIN edit.ixn_qualifier ixnQualifier ON cc.chem_conc_exp_route_id = chemConcExpRoute.id -- INNER JOIN edit.action_type actionType -- INNER JOIN ixn_qualifier ixnQualifier ON cc.ixn_qualifier_id = ixnQualifier.id -- left_outer join ixn i ON cc.ixn_id = i.id ON cc.ixn_qualifier_id = ixnQualifier.id -- INNER JOIN pub1.term diseaseTerm -- ,ixn_actor ia ------------------------------------------------------ -- WHERE cc.chem_acc_txt = chemTerm.acc_txt -- AND cc.chem_acc_db_id = chemTerm.acc_db_id -- AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) -- ------------------------------------------------------ -- AND cc.taxon_acc_txt = taxonTerm.acc_txt -- AND cc.taxon_acc_db_id = taxonTerm.acc_db_id -- AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) ------------------------------------------------------ --AND cc.disease_acc_txt = diseaseTerm.acc_txt --AND cc.disease_acc_db_id = diseaseTerm.acc_db_id --AND diseaseTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'disease' ) ------------------------------------------------------ --AND cc.chem_conc_exp_route_id = chemConcExpRoute.id ------------------------------------------------------ --AND cc.ixn_qualifier_id = ixnQualifier.id ------------------------------------------------------ limit 100 select distinct chem_conc_exp_route_id, count(*) from chem_conc cc group by chem_conc_exp_route_id order by chem_conc_exp_route_id
Date: 2026-01-20 15:13:27
Statement: SELECT cc.id -- id ,cc.reference_acc_txt -- reference_acc_txt ,cc.reference_acc_db_id -- reference_acc_db_id ,cc.chem_acc_txt -- chem_acc_txt ,cc.chem_acc_db_id -- chem_acc_db_id ,chemTerm.nm -- chem_nm ,chemTerm.nm_html -- chem_nm_html ,cc.chem_conc -- chem_conc ,cc.chem_conc_range -- chem_conc_range ,cc.taxon_acc_txt -- taxon_acc_txt ,cc.taxon_acc_db_id -- taxon_acc_db_id ,taxonTerm.nm -- taxon_nm ,taxonTerm.nm_html -- taxon_nm_html ,diseaseTerm.nm -- disease_nm ,diseaseTerm.nm_html -- disease_nm_html ,actionType.cd -- action_type_cd ,chemConcExpRoute.nm -- chem_conc_exp_route_nm ,ixnQualifier.nm -- ixn_qualifier_nm ,cc.note -- note ,cc.chem_co_nm -- chem_co_nm ,cc.chem_catalog_nbr -- chem_catalog_nbr ------------------------------------------------------ FROM load.chem_conc cc INNER JOIN pub2.term chemTerm ON cc.chem_acc_txt = chemTerm.acc_txt AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) INNER JOIN pub2.term taxonTerm ON cc.taxon_acc_txt = taxonTerm.acc_txt AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) left OUTER JOIN edit.chem_conc_exp_route chemConcExpRoute ON cc.chem_conc_exp_route_id = chemConcExpRoute.id INNER JOIN edit.ixn_qualifier ixnQualifier ON cc.ixn_qualifier_id = ixnQualifier.id INNER JOIN ixn_qualifier ixnQualifier ON cc.ixn_qualifier_id = ixnQualifier.id left_outer join ixn i ON cc.ixn_id = i.ixn_id -- don't need root_id here - there are binary relationships INNER JOIN edit.ixn_action ia ON i.ixn_id = ia.ixn_id INNER JOIN edit.action_type actionType ON ia.action_type_id = actionType.id INNER JOIN edit.ixn_actor actor ON ia.ixn_id = actor.ixn_id AND actor.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'disease' ) INNER JOIN pub2.term diseaseTerm ON actor.acc_txt = diseaseTerm.acc_txt AND actor.object_type_id = diseaseTerm.object_type_id ------------------------------------------------------ -- WHERE cc.chem_acc_txt = chemTerm.acc_txt -- AND cc.chem_acc_db_id = chemTerm.acc_db_id -- AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) -- ------------------------------------------------------ -- AND cc.taxon_acc_txt = taxonTerm.acc_txt -- AND cc.taxon_acc_db_id = taxonTerm.acc_db_id -- AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) ------------------------------------------------------ --AND cc.disease_acc_txt = diseaseTerm.acc_txt --AND cc.disease_acc_db_id = diseaseTerm.acc_db_id --AND diseaseTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'disease' ) ------------------------------------------------------ --AND cc.chem_conc_exp_route_id = chemConcExpRoute.id ------------------------------------------------------ --AND cc.ixn_qualifier_id = ixnQualifier.id ------------------------------------------------------ limit 100
Date: 2026-01-20 16:30:07
Statement: select count(*) from pub2..chem_conc
Date: 2026-01-21 10:03:21 Database: ctddev51 Application: pgAdmin 4 - CONN:8720644 User: load Remote:
6 5 ERROR: missing FROM-clause entry for table "..."
Times Reported Most Frequent Error / Event #6
Day Hour Count Jan 20 10 2 16 3 - ERROR: missing FROM-clause entry for table "chemconcexproute" at character 2392
- ERROR: missing FROM-clause entry for table "atd" at character 39
- ERROR: missing FROM-clause entry for table "atd" at character 39
Statement: ------------------------------------------------------ SELECT cc.id -- id ,cc.reference_acc_txt -- reference_acc_txt ,cc.reference_acc_db_id -- reference_acc_db_id ,cc.chem_acc_txt -- chem_acc_txt ,cc.chem_acc_db_id -- chem_acc_db_id ,chemTerm.nm -- chem_nm ,chemTerm.nm_html -- chem_nm_html ,cc.chem_conc -- chem_conc ,cc.chem_conc_range -- chem_conc_range ,cc.taxon_acc_txt -- taxon_acc_txt ,cc.taxon_acc_db_id -- taxon_acc_db_id ,taxonTerm.nm -- taxon_nm ,taxonTerm.nm_html -- taxon_nm_html -- ,cc.disease_acc_txt -- disease_acc_txt -- ,cc.disease_acc_db_id -- disease_acc_db_id -- ,diseaseTerm.nm -- disease_nm -- ,diseaseTerm.nm_html -- disease_nm_html -- ,chemConcExpRoute.exp_route -- chem_conc_exp_route_nm ,ixnQualifier.nm -- ixn_qualifier_nm ,cc.note -- note -- ,actionType.cd -- action_type_cd ,cc.chem_co_nm -- chem_co_nm ,cc.chem_catalog_nbr -- chem_catalog_nbr ------------------------------------------------------ FROM load.chem_conc cc INNER JOIN pub1.term chemTerm ON cc.chem_acc_txt = chemTerm.acc_txt AND -- cc.chem_acc_db_id = chemTerm.acc_db_id AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) INNER JOIN pub1.term taxonTerm ON cc.taxon_acc_txt = taxonTerm.acc_txt AND -- cc.taxon_acc_db_id = taxonTerm.acc_db_id AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) -- left OUTER JOIN edit.chem_conc_exp_route chemConcExpRoute ON cc.chem_conc_exp_route_id = chemConcExpRoute.id INNER JOIN edit.ixn_qualifier ixnQualifier ON cc.chem_conc_exp_route_id = chemConcExpRoute.id -- INNER JOIN edit.action_type actionType -- INNER JOIN ixn_qualifier ixnQualifier ON cc.ixn_qualifier_id = ixnQualifier.id -- left_outer join ixn i ON cc.ixn_id = i.id ON cc.ixn_qualifier_id = ixnQualifier.id -- INNER JOIN pub1.term diseaseTerm -- ,ixn_actor ia ------------------------------------------------------ -- WHERE cc.chem_acc_txt = chemTerm.acc_txt -- AND cc.chem_acc_db_id = chemTerm.acc_db_id -- AND chemTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'chem' ) -- ------------------------------------------------------ -- AND cc.taxon_acc_txt = taxonTerm.acc_txt -- AND cc.taxon_acc_db_id = taxonTerm.acc_db_id -- AND taxonTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'taxon' ) ------------------------------------------------------ --AND cc.disease_acc_txt = diseaseTerm.acc_txt --AND cc.disease_acc_db_id = diseaseTerm.acc_db_id --AND diseaseTerm.object_type_id = ( SELECT id FROM edit.object_type WHERE cd = 'disease' ) ------------------------------------------------------ --AND cc.chem_conc_exp_route_id = chemConcExpRoute.id ------------------------------------------------------ --AND cc.ixn_qualifier_id = ixnQualifier.id ------------------------------------------------------ limit 100
Date: 2026-01-20 10:43:57 Database: ctddev51 Application: pgAdmin 4 - CONN:909476 User: load Remote:
Statement: select ia.* ,at.cd ,at.* ,atd.cd from edit.ixn_action ia ,edit.action_type at ,edit.action_degree_type adt where ia.ixn_id = 8382512 and ia.action_type_id = at.id and ia.action_degree_type_id = adt.id limit 100
Date: 2026-01-20 16:03:46
Statement: select ia.* ,at.cd ,at.* ,atd.* from edit.ixn_action ia ,edit.action_type at ,edit.action_degree_type adt where ia.ixn_id = 8382512 and ia.action_type_id = at.id and ia.action_degree_type_id = adt.id limit 100
Date: 2026-01-20 16:03:55
7 3 ERROR: function count(...) does not exist
Times Reported Most Frequent Error / Event #7
Day Hour Count Jan 21 16 3 - ERROR: function count(character varying, integer, character varying, integer, character varying, character varying, character varying, numrange, character varying, integer, character varying, character varying, character varying, integer, character varying, character varying, character varying, character varying, character varying, character varying, character varying, character varying) does not exist at character 8
- ERROR: function count(character varying, integer) does not exist at character 8
- ERROR: function count(character varying, integer, character varying, integer, character varying, character varying, character varying, numrange, character varying, integer, character varying, character varying, character varying, integer, character varying, character varying, character varying, character varying, character varying, character varying, character varying, character varying, character varying) does not exist at character 8
Hint: No function matches the given name and argument types. You might need to add explicit type casts.
Statement: select count( distinct reference_acc_txt ,reference_acc_db_id ,chem_acc_txt ,chem_acc_db_id ,chem_nm ,chem_nm_html ,chem_conc ,chem_conc_range ,taxon_acc_txt ,taxon_acc_db_id ,taxon_nm ,taxon_nm_html ,disease_acc_txt ,disease_acc_db_id ,disease_nm ,disease_nm_html ,chem_conc_exp_route_nm ,ixn_qualifier_nm ,note ,action_type_cd ,chem_co_nm ,chem_catalog_nbr ) from pub2.chem_concDate: 2026-01-21 16:45:23
Hint: No function matches the given name and argument types. You might need to add explicit type casts.
Statement: select count( distinct reference_acc_txt ,reference_acc_db_id ) from pub2.chem_concDate: 2026-01-21 16:46:54
Hint: No function matches the given name and argument types. You might need to add explicit type casts.
Statement: select count( reference_acc_txt ,reference_acc_db_id ,chem_acc_txt ,chem_acc_db_id ,chem_nm ,chem_nm_html ,chem_conc ,chem_conc_range ,taxon_acc_txt ,taxon_acc_db_id ,taxon_nm ,taxon_nm_html ,disease_acc_txt ,disease_acc_db_id ,disease_nm ,disease_nm_html ,chem_conc_exp_route_nm ,ixn_qualifier_nm ,note ,action_type_cd ,chem_co_nm ,chem_catalog_nbr ,cca.anatomy_acc_txt ) from pub2.chem_conc cc ,pub2.chem_conc_anatomy cca where cc.id = cca.chem_conc_idDate: 2026-01-21 16:53:26
8 3 ERROR: insert or update on table "..." violates foreign key constraint "..."
Times Reported Most Frequent Error / Event #8
Day Hour Count Jan 20 10 1 11 2 - ERROR: insert or update on table "chem_conc_anatomy" violates foreign key constraint "chem_conc_chem_conc_anatomy_fk"
Detail: Key (chem_conc_id)=(8019) is not present in table "chem_conc".
Statement: insert into chem_conc_anatomy values (8019, 'D006352', 21, 'Heart Ventricles', 0)Date: 2026-01-20 10:58:17
9 2 ERROR: constraint "..." for relation "..." already exists
Times Reported Most Frequent Error / Event #9
Day Hour Count Jan 20 10 1 11 1 - ERROR: constraint "chem_conc_chem_conc_anatomy_fk" for relation "chem_conc_anatomy" already exists
Statement: ALTER TABLE chem_conc_anatomy ADD CONSTRAINT chem_conc_chem_conc_anatomy_fk FOREIGN KEY (chem_conc_id) REFERENCES chem_conc(id) ;
Date: 2026-01-20 10:50:14 Database: ctddev51 Application: pgAdmin 4 - CONN:4218531 User: load Remote:
10 2 ERROR: cannot truncate a table referenced in a foreign key constraint
Times Reported Most Frequent Error / Event #10
Day Hour Count Jan 20 10 1 11 1 - ERROR: cannot truncate a table referenced in a foreign key constraint
Detail: Table "chem_conc_anatomy" references "chem_conc".
Hint: Truncate table "chem_conc_anatomy" at the same time, or use TRUNCATE ... CASCADE.
Statement: truncate table load.chem_concDate: 2026-01-20 10:59:38
11 2 ERROR: VACUUM cannot run inside a transaction block
Times Reported Most Frequent Error / Event #11
Day Hour Count Jan 23 09 1 11 1 - ERROR: VACUUM cannot run inside a transaction block
- ERROR: VACUUM cannot run inside a transaction block
Statement: TRUNCATE TABLE ctd_reference; ALTER SEQUENCE ctd_reference_id_seq RESTART; -- articles INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt -- Is this reference contained in the REFERENCE table? ,is_in_ctd -- Is this reference the one to be used for citing CTD? ,is_primary_citation ,acc_txt ,acc_db_cd ,type_cd ) VALUES ('Integrating AI-powered text mining from PubTator into the manual curation workflow at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2025 Feb 21.' ,'Wiegers TC, Davis AP, Wiegers J, Sciaky D, Barkalow F, Wyatt B, Strong M, McMorran R, Abrar S, Mattingly CJ' ,'2025-02-21' ,false ,FALSE ,'39982792' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database’s 20th anniversary: update 2025.' ,'Nucleic Acids Res. 2024 Oct 10.' ,'Davis AP, Wiegers TC, Sciaky D, Barkalow F, Strong M, Wyatt B, Wiegers J, McMorran R, Abrar S, Mattingly CJ' ,'2024-10-10' ,false ,TRUE ,'39385618' ,'PUBMED' ,'a' ) ,('Transforming environmental health datasets from the comparative toxicogenomics database into chord diagrams to visualize molecular mechanisms.' ,'Front. Toxicol., 21 July 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers J, Abrar S, Sciaky D, Barkalow F, Strong M, Mattingly CJ' ,'2024-07-21' ,false ,FALSE ,'39104826' ,'PUBMED' ,'a' ) ,('CTD Tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health.' ,'Toxicol Sci. 2023 Jul 24:kfad069.' ,'Davis AP, Wiegers TC, Wiegers J, Wyatt B, Johnson RJ, Sciaky D, Barkalow F, Strong M, Planchart A, Mattingly CJ' ,'2023-07-24' ,false ,FALSE ,'37486259' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database (CTD): update 2023.' ,'Nucleic Acids Res. 2022 Sep 28.' ,'Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ' ,'2022-09-28' ,false ,TRUE ,'36169237' ,'PUBMED' ,'a' ) ,('Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the comparative toxicogenomics database.' ,'Curr Res Toxicol.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ' ,'2021-08-05' ,false ,FALSE ,'34458863' ,'PUBMED' ,'a' ) ,('Regulatory Status of Pesticide Residues in Cannabis: Implications to Medical Use in Neurological Diseases.' ,'Curr Res Toxicol. Volume 2, 2021, Pages 140-148.' ,'Pinkhasova DV, Jameson LE, Conrow KD, Simeone MP, Davis AP, Wiegers TC, Mattingly CJ, Leung MCK' ,'2021-07-22' ,false ,FALSE ,'34308371' ,'PUBMED' ,'a' ) ,('CTD anatomy: Analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies.' ,'Curr Res Toxicol. Volume 2, 2021, Pages 128-139.' ,'Davis AP, Wiegers TC, Wiegers J, Grondin CJ, Johnson RJ, Sciaky D, Mattingly CJ' ,'2021-03-06' ,false ,FALSE ,'33768211' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2021.' ,'Nucleic Acids Res. 2020 Oct 17.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Wiegers TC, Mattingly CJ' ,'2020-10-17' ,false ,FALSE ,'33068428' ,'PUBMED' ,'a' ) ,('Leveraging the Comparative Toxicogenomics Database to fill in knowledge gaps for environmental health: a test case for air pollution-induced cardiovascular disease.' ,'Toxicol Sci. 2020 Jul 14.' ,'Davis AP, Wiegers TC, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ' ,'2020-07-14' ,false ,FALSE ,'32663284' ,'PUBMED' ,'a' ) ,('Public data sources to support systems toxicology applications.' ,'Curr Opin Toxicol. 2019 August 16:17-24.' ,'Davis AP, Wiegers J, Wiegers TC, Mattingly CJ' ,'2019-08-16' ,false ,FALSE ,'33604492' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2019.' ,'Nucleic Acids Res. 2018 Sep 24.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ' ,'2018-09-24' ,false ,FALSE ,'30247620' ,'PUBMED' ,'a' ) ,('Chemical-induced phenotypes at CTD help inform the pre-disease state and construct adverse outcome pathways.' ,'Toxicol Sci. 2018 May 28.' ,'Davis AP, Wiegers TC, Wiegers J, Johnson RJ, Sciaky D, Grondin CJ, Mattingly CJ' ,'2018-05-28' ,false ,false ,'29846728' ,'PUBMED' ,'a' ) ,('Accessing an Expanded Exposure Science Module at the Comparative Toxicogenomics Database.' ,'Environ Health Perspect. 2018 Jan 18;126(1):014501.' ,'Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ' ,'2018-01-18' ,false ,false ,'29351546' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2017.' ,'Nucleic Acids Res. 2016 Sep 19;[Epub ahead of print]' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, King BL, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ.' ,'2016-10-03' ,false ,FALSE ,'27651457' ,'PUBMED' ,'a' ) ,('Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database.' ,'Environ Health Perspect. 2016 May 12' ,'Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ.' ,'2016-05-12' ,false ,false ,'27170236' ,'PUBMED' ,'a' ) ,('Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.' ,'PLoS One. 2016 May 12;11(5):e0155530.' ,'Davis AP, Wiegers TC, King BL, Wiegers J, Grondin CJ, Sciaky D, Johnson RJ, Mattingly CJ.' ,'2016-05-12' ,false ,false ,'27171405' ,'PUBMED' ,'a' ) ,('ToxEvaluator: an integrated computational platform to aid the interpretation of toxicology study-related findings.' ,'Database (Oxford). 2016 May 9;2016. pii: baw062.' ,'Pelletier D, Wiegers TC, Enayetallah A, Kibbey C, Gosink M, Koza-Taylor P, Mattingly CJ, Lawton M.' ,'2016-05-10' ,false ,false ,'27161010' ,'PUBMED' ,'a' ) ,('Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task.' ,'Database (Oxford). 2016 Mar 19;2016. pii: baw032.' ,'Wei CH, Peng Y, Leaman R, Davis AP, Mattingly CJ, Li J, Wiegers TC, Lu Z.' ,'2016-03-19' ,false ,false ,'26994911' ,'PUBMED' ,'a' ) ,('BioCreative V CDR task corpus: a resource for chemical disease relation extraction.' ,'Database (Oxford). 2016 May 9;2016. pii: baw068' ,'Li J, Sun Y, Johnson RJ, Sciaky D, Wei CH, Leaman R, Davis AP, Mattingly CJ, Wiegers TC, Lu Z.' ,'2016-05-09' ,false ,false ,'27161011' ,'PUBMED' ,'a' ) ,('Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences.' ,'Environ Health Perspect. 2016 Feb 12.' ,'Mattingly CJ, Boyles R, Lawler CP, Haugen AC, Dearry A, Haendel M.' ,'2016-02-12' ,false ,false ,'26871594' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database''s 10th year anniversary: update 2015.' ,'Nucleic Acids Res. 2015 Jan;43 (Database issue): D914-20.' ,'Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ.' ,'2015-01-01' ,false ,FALSE ,'25326323 ' ,'PUBMED' ,'a' ) ,('Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.' ,'Database (Oxford). 2014 Jun 10:bau050.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2014-06-10' ,false ,false ,24919658 ,'PUBMED' ,'a' ) ,('BioC interoperability track overview.' ,'Database (Oxford). 2014 Jun 30:bau053.' ,'Comeau DC, Batista-Navarro RT, Dai HJ, Dogan RI, Yepes AJ, Khare R, Lu Z, Marques H, Mattingly CJ, Neves M, Peng Y, Rak R, Rinaldi F, Tsai RT, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.' ,'2014-06-09' ,false ,false ,24980129 ,'PUBMED' ,'a' ) ,('BioCreative-IV virtual issue.' ,'Database (Oxford). 2014 May 22:bau039.' ,'Arighi CN, Wu CH, Cohen KB, Hirschman L, Krallinger M, Valencia A, Lu Z, Wilbur JW, Wiegers TC' ,'2014-05-22' ,false ,false ,24852177 ,'PUBMED' ,'a' ) ,('A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.' ,'Database (Oxford). 2013 Nov 28:bat080.' ,'Davis AP, Wiegers TC, Roberts PM, King BL, Lay JM, Lennon-Hopkins K, Sciaky D, Johnson R, Keating H, Greene N, Hernandez R, McConnell KJ, Enayetallah AE, Mattingly CJ.' ,'2013-11-28' ,false ,false ,'24288140' ,'PUBMED' ,'a' ) ,('Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.' ,'Proceedings of the Fourth BioCreative Evaluation Workshop 1: 69-84.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2013-10-06' ,false ,false ,NULL ,NULL ,'a' ) ,('BioC: a minimalist approach to interoperability for biomedical text processing.' ,'Database (Oxford). 2013 Sep 18:bat064.' ,'Comeau DC, Islamaj DR, Ciccarese P, Cohen KB, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M, Valencia A, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.' ,'2013-09-18' ,false ,false ,'24048470' ,'PUBMED' ,'a' ) ,('Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the Comparative Toxicogenomics Database.' ,'PLoS One. 2013 Apr 17;8(4):e58201.' ,'Davis AP, Wiegers TC, Johnson RJ, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, Murphy CG, Mattingly CJ.' ,'2013-04-17' ,false ,false ,'23613709' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2013.' ,'Nucleic Acids Res. 2013 Jan 1;41(D1):D1104-14.' ,'Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2013-01-01' ,false ,FALSE ,'23093600' ,'PUBMED' ,'a' ) ,('Targeted journal curation as a method to improve data currency at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2012 Dec 6;2012:bas051.' ,'Davis AP, Johnson RJ, Lennon-Hopkins K, Sciaky D, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-12-06' ,false ,false ,'23221299' ,'PUBMED' ,'a' ) ,('Collaborative biocuration--text-mining development task for document prioritization for curation.' ,'Database (Oxford). 2012 Nov 22;2012:bas037.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2012-11-22' ,false ,false ,'23180769' ,'PUBMED' ,'a' ) ,('Ranking Transitive Chemical-Disease Inferences Using Local Network Topology in the Comparative Toxicogenomics Database.' ,'PLoS One. 2012;7(11):e46524.' ,'King BL, Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-11-07' ,false ,false ,'23144783' ,'PUBMED' ,'a' ) ,('Text mining for the biocuration workflow.' ,'Database (Oxford). 2012 Apr 18;2012:bas020.' ,'Hirschman L, Burns GA, Krallinger M, Arighi C, Cohen KB, Valencia A, Wu CH, Chatr-Aryamontri A, Dowell KG, Huala E, Lourenço A, Nash R, Veuthey AL, Wiegers T, Winter AG.' ,'2012-04-18' ,false ,false ,'22513129' ,'PUBMED' ,'a' ) ,('MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2012 Mar 20;2012:bar065.' ,'Davis AP, Wiegers TC, Rosenstein MC, Mattingly CJ.' ,'2012-03-20' ,false ,false ,'22434833' ,'PUBMED' ,'a' ) ,('Disease model curation improvements at Mouse Genome Informatics.' ,'Database (Oxford). 2012 Mar 20;2012:bar063.' ,'Bello SM, Richardson JE, Davis AP, Wiegers TC, Mattingly CJ, Dolan ME, Smith CL, Blake JA, Eppig JT.' ,'2012-03-20' ,false ,false ,'22434831' ,'PUBMED' ,'a' ) ,('Providing the Missing Link: the Exposure Science Ontology ExO.' ,'Environ Sci Technol. 2012 Mar 20;46(6):3046-53.' ,'Mattingly CJ, McKone TE, Callahan MA, Blake JA, Cohen Hubal EA.' ,'2012-03-20' ,false ,false ,'22324457' ,'PUBMED' ,'a' ) ,('DiseaseComps: a metric that discovers similar diseases based upon common toxicogenomic profiles at CTD.' ,'Bioinformation. 2011 Oct 14;7(4):154-6.' ,'Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2011-10-14' ,false ,false ,'22125387' ,'PUBMED' ,'a' ) ,('The curation paradigm and application tool used for manual curation of the scientific literature at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2011 Sep 20;2011:bar034.' ,'Davis AP, Wiegers TC, Rosenstein MC, Murphy CG, Mattingly CJ.' ,'2011-09-20' ,false ,false ,'21933848' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2011.' ,'Nucleic Acids Res. 2011 Jan;39(Database issue):D1067-72.' ,'Davis AP, King BL, Mockus S, Murphy CG, Saraceni-Richards C, Rosenstein M, Wiegers T, Mattingly CJ.' ,'2011-01-01' ,false ,false ,'20864448' ,'PUBMED' ,'a' ) ,('GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles.' ,'Bioinformation. 2009 Oct 15;4(4):173-4.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Hampton TH, Mattingly CJ.' ,'2009-10-15' ,false ,false ,'20198196' ,'PUBMED' ,'a' ) ,('Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD).' ,'BMC Bioinformatics. 2009 Oct 8;10(1):326.' ,'Wiegers TC, Davis AP, Cohen KB, Hirschman L, Mattingly CJ. ' ,'2009-10-08' ,false ,false ,'19814812' ,'PUBMED' ,'a' ) ,('Genetic and environmental pathways to complex diseases.' ,'BMC Syst Biol. 2009 May 5;3(1):46.' ,'Gohlke JM, Thomas R, Zhang Y, Rosenstein MC, Davis AP, Murphy C, Becker KG, Mattingly CJ, Portier CJ.' ,'2009-05-05' ,false ,false ,'19416532' ,'PUBMED' ,'a' ) ,('Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos.' ,'Environ Health Perspect. 2009 Jun;117(6):981-7.' ,'Mattingly CJ, Hampton T, Brothers K, Griffin NE, Planchart AJ.' ,'2009-06-01' ,true ,false ,'19590694' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks.' ,'Nucleic Acids Res. 2009 Jan;37(Database issue):D786-92.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ. ' ,'2009-01-01' ,false ,false ,'18782832' ,'PUBMED' ,'a' ) ,('Chemical databases for environmental health and clinical research.' ,'Toxicol Lett. 2009 Apr 10;186(1):62-5.' ,'Mattingly CJ.' ,'2009-04-10' ,false ,false ,'18996453' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study.' ,'BMC Med Genomics. 2008 Oct 9;1(1):48.' ,'Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2008-10-09' ,false ,false ,'18845002' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies.' ,'J Exp Zoolog A Comp Exp Biol. 2006 Sep 1;305(9):689-92.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2006-09-01' ,false ,false ,'16902965' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: a cross-species resource for building chemical-gene interaction networks.' ,'Toxicol Sci. 2006 Aug;92(2):587-95.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Colby GT, Forrest JN, Boyer JL.' ,'2006-08-01' ,false ,false ,'16675512' ,'PUBMED' ,'a' ) ,('Promoting comparative molecular studies in environmental health research: an overview of the comparative toxicogenomics database (CTD).' ,'Pharmacogenomics J. 2004;4(1):5-8.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2004-01-01' ,false ,false ,'14735110' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Environ Health Perspect. 2003 May;111(6):793-5.' ,'Mattingly CJ, Colby GT, Forrest JN, Boyer JL.' ,'2003-05-01' ,false ,false ,'12760826' ,'PUBMED' ,'a' ) ; -- Online publications INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt ,type_cd ,url ) VALUES ('Linking chemical data from the Comparative Toxicogenomics Database with adverse outcome pathways from the AOP-Wiki: a mechanistic data-oriented approach to help inform environmental health.' ,'F1000Research 2025, 14:1266 (2025)' ,'Davis AP, Wiegers TC, Sciaky D, Barkalow F, Wyatt B, Wiegers J, McMorran R, Abrar S, Mattingly CJ' ,'2025-11-17' ,'a' ,'' ) ,('Understanding environment-disease connections: An introduction to the Comparative Toxicogenomics Database (CTD).' ,'NCI-Nature Pathway Interaction Database. doi:10.1038/pid.2011.2 (2011).' ,'Mattingly CJ.' ,'2011-06-01' ,'a' ,'https://doi.org/10.12688/f1000research.172567.1' ) ; -- Posters/presentations INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt ,type_cd ,url ,abstract_url ) VALUES ('Using the Comparative Toxicogenomics Database (CTD) to explore air pollution-associated adverse pregnancy outcomes by integrating exposure data with toxicological mechanisms.' ,'International Society of Exposure Science. Atlanta, GA. August 17-20, 2025.' ,'Mattingly CJ, Abrar S, Barkalow F, Sciaky D, Wiegers JA, Wyatt B, Wiegers TC, Davis AP.' ,'August 17, 2025' ,'p' ,NULL ,NULL ) ,('Using CTD to provide environmental chemical content and inform adverse outcome pathways from the AOP-Wiki.' ,'2025 EHLC Workshop on AOP Standards. Virtual. June 4-5, 2025.' ,'Davis AP.' ,'June 4, 2025' ,'p' ,NULL ,NULL ) ,('Exploring environmental influences on Alzheimer’s disease using the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Mattingly CJ, Abrar S, Barkalow F, Sciaky D, Strong M, Wiegers JA, Wyatt B, Wiegers TC, Davis AP.' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a resource to distill complex exposure pathways to help inform the environmental health continuum, from populations to molecules.' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Davis AP, Wyatt B, Wiegers TC, Wiegers J, Sciaky D, Barkalaw F, Strong, M, Abrar S, Mattingly CJ.' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to distill exposure information, from molecular mechanisms to populations.' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Davis AP' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a resource to distill complex exposure pathways to help inform the environmental health continuum, from populations to molecules.' ,'International Society of Exposure Science. Montreal, Quebec, Canada. October 20-24, 2024.' ,'Davis AP, Wyatt B, Wiegers TC, Wiegers J, Sciaky D, Barkalaw F, Strong, M, Abrar S, Mattingly CJ.' ,'October 20, 2024' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a public resource to understand the health effects of PFAS.' ,'National PFAS Conference. Ann Arbor, MI, USA. June 10-12, 2024.' ,'Mattingly CJ, Sciaky D, Barkalaw F, Wyatt B, Strong, M, McMorran R, Abrar S, Wiegers J, Wiegers TC, Davis AP.' ,'June 10, 2024' ,'p' ,NULL ,NULL ) ,('CTD Tetramers: filling environmental health knowledge gaps with computed molecular mechanisms.' ,'NIH/NLM/NCBI Journal Club. Virtual. May 22, 2024.' ,'Davis AP.' ,'May 22, 2024' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database: A tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.' ,'Sapporo Exposome. Sopporo, Japan. May 24-27, 2024.' ,'Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP.' ,'May 24, 2024' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD).' ,'NINDS, NIEHS, UDN, and External Experts Environmental Trigger Workshop. Virtual. May 6, 2024.' ,'Mattingly CJ.' ,'May 6, 2024' ,'p' ,NULL ,NULL ) ,('CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.' ,'DRKB Program Network Meeting. Rockville, MD, USA. February 28-29, 2024.' ,'Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP' ,'February 28, 2024' ,'p' ,NULL ,NULL ) ,('CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.' ,'Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.' ,'Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Wyatt B, Abrat S, Mattingly CJ.' ,'March 10, 2024' ,'p' ,NULL ,NULL ) ,('Surveying environmental influences for Alzheimer disease using the public Comparative Toxicogenomics Database.' ,'Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.' ,'March 10, 2024' ,'p' ,NULL ,NULL ) ,('CTD integrates curated chemical, gene, phenotype, anatomy, disease, and exposure data to fill knowledge gaps for environmental health: PFAS-childhood asthma as a use case.' ,'USA Exposome Symposium: Children’s Health, Environmental Justice, and the Exposome. Nashville, TN, USA. January 22-24, 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.' ,'January 22, 2024' ,'p' ,NULL ,NULL ) ,('Using CTD to fill knowledge gaps for environmental neuroscience.' ,'NIH Environmental Neuroscience Working Group. Virtual. August 29 2023.' ,'Davis AP.' ,'August 29 2023' ,'p' ,NULL ,NULL ) ,('Using CTD to fill knowledge gaps for environmental health.' ,'Jonathan Hamm Lab Seizure Project Meeting. Virtual. December 15, 2023.' ,'Davis AP.' ,'December 15, 2023' ,'p' ,NULL ,NULL ) ,('CTD Tetramers: a new online tool to fill knowledge gaps about environmental health.' ,'Society of Toxicology 62nd Annual Meeting. Nashville, TN, USA. March 19-23, 2023.' ,'Mattingly CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 19, 2023' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database: a tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.' ,'Alzheimer’s Association International Conference. Amsterdam, Netherlands. July 16-20, 2023.' ,'Mattingly CJ, Wiegers TC, Wiegers JA, Sciaky D, Johnson RJ, Davis AP. ' ,'July 16, 2023' ,'p' ,NULL ,NULL ) ,('Introduction to CTD: navigating curated data t fill in knowledge gaps for environmental health.' ,'The Jackson Laboratory. Bar Harbor, ME, USA. July 12, 2022' ,'Davis AP.' ,'July 12, 2022' ,'p' ,NULL ,NULL ) ,('CTD: integrating chemical, gene, phenotype, anatomy, disease, and exposure data to fill in knowledge gaps for environmental health' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Analyzing e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database.' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Davis AP, Grondin CJ, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Mechanism of neurological hazards from insecticide exposure in cannabis.' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Jameson L, Rivera A, Conrow K, Pinkhasova D, Jourachian N, Johnson S, Davis AP, Wiegers T, Sammi S, Mattingly CJ, Afia I, Orser C, Cannon J, Leung M.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Leveraging CTD data to fill in knowledge gaps for environmental health.' ,'OpenTox Euro. Virtual. September 24, 2021.' ,'Davis AP.' ,'September 24, 2021' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): linking chemicals, genes, phenotypes, diseases, and exposures to fill in knowledge gaps for environmental health.' ,'Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 12, 2021' ,'p' ,NULL ,NULL ) ,('Regulatory status of pesticide residues I cannabis: implications to medical use in neurological diseases.' ,'Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.' ,'Pinkhasova S, Jameson L, Conrow K, Simeone M, Davis AP, Wiegers T, Mattingly CJ, Leung M.' ,'March 12, 2021' ,'p' ,NULL ,NULL ) ,('Analyzing the Effects of Emerging Environmental Exposures on Human Health Using the Comparative Toxicogenomics Database.' ,'International Society of Exposure Science. Virtual. August 30-September 2, 2021.' ,'Grondin C, Davis AP, Johnson R, Sciaky D, Wiegers J, Wiegers T, Mattingly CJ. ' ,'August 30, 2021' ,'p' ,NULL ,NULL ) ,('Introduction to CTD.' ,'Arizona State University. Virtual. March 18, 2021.' ,'Davis AP.' ,'March 18, 2021' ,'p' ,NULL ,NULL ) ,('Leveraging CTD to fill in knowledge gaps for environmental health science.' ,'NTP Data Science Seminar Series. Virtual. June 19, 2021.' ,'Davis AP.' ,'June 19, 2021' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a comprehensive view of chemical exposures, mechanisms, and biological effects.' ,'Society of Toxicology 59th Annual Meeting. Virtual. March 15-19, 2020.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 15, 2020' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): mechanism meets exposure science illustrated through a bisphenol A-diabetes case study.' ,'Society of Toxicology 58th Annual Meeting. Baltimore, MD, USA. March 11-14, 2019.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 11, 2019' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to further our understanding of environmental exposures on human health.' ,'International Society of Exposure Science. Ottawa, Canada. August 27-29, 2018.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Johnson RJ, Sciaky D, Mattingly CJ. ' ,'August 27, 2018' ,'p' ,NULL ,NULL ) ,('Chemical-induced phenotypes at CTD: informing the pre-disease state and adverse outcome pathways.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Mattingly CJ. ' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): an integrated resource for chemical, gene, phenotype, and exposure data.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Facilitating exposure data analysis in the Comparative Toxicogenomics Database: a case study of heavy metals and metabolic syndrome.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Green A, Planchart A, Mattingly CJ.' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): integrating chemical, gene, phenotype, disease, and exposure science data.' ,'Society of Toxicology 56th Annual Meeting. Baltimore, MD, USA. March 12-16, 2017.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.' ,'March 12, 2017' ,'p' ,NULL ,NULL ) ,('Chemical-phenotype curation at the Comparative Toxicogenomics Database.' ,'10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.' ,'Davis AP, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'March 26, 2017' ,'p' ,NULL ,NULL ) ,('Exposure science in CTD: linking chemical stressors to outcomes via an Exposure Ontology.' ,'10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.' ,'Grondin CJ, Davis AP, Wiegers J, Wiegers, TC, King BL, Mattingly CJ.' ,'March 26, 2017' ,'p' ,NULL ,NULL ) ,('Curation and integration of exposure science at the Comparative Toxicogenomics Database: an introduction for new users.' ,'Emory Exposome Summer Course. Atlanta, GA, USA. June 13-15, 2016.' ,'Davis AP.' ,'June 13, 2016' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Expanding Exposome and Phenotype Content to Elucidate Chemical-Disease Relationships.' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.' ,'Mattingly CJ, Grondin CJ, Johnson R, Sciaky D, King BL, Wiegers JA, Wiegers TC, Davis AP.' ,'2016-03-18' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Advancing understanding of molecular connections among chemicals, genes and diseases.' ,'American Chemical Society National Meeting. San Diego, CA, USA Mar 13-17, 2016.' ,'Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ.' ,'2016-03-17' ,'p' ,NULL ,NULL ) ,('Elucidating Correlations between High-Throughput Chemical Screening and Curated Literature.' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.' ,'Collier G, Planchart A, Reif DM, Mattingly CJ.' ,'2016-03-16' ,'p' ,NULL ,NULL ) ,('BioCreative V Track 3: Chemical-Disease Relation AND Disease Named Entity Recognition and Normalization.' ,'BioCreative V Challenge Workshop. cicCartuja, Sevilla, Spain. Sept 9-11, 2015.' ,'Wiegers TC, Lu, Z.' ,'2015-09-10' ,'p' ,NULL ,NULL ) ,( 'Exposure Science Data and the Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'2015-03-22' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database: Ten Years in the Making.' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.' ,'Mattingly CJ, Grondin CJ, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, Wiegers JA, McMorran R, King BL, Wiegers TC, Davis AP.' ,'2015-03-22' ,'p' ,NULL ,NULL ) ,( 'Exposure data and the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Grondin CJ, Davis AP, Mattingly CJ.' ,'2014-03-25' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Davis AP, Mattingly CJ, Murphy CG, Lay JM, Lennon-Hopkins K, Sciaky D, Saracini-Richards C, King BL, Rosenstein MC, Wiegers TC.' ,'2014-03-24' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database (CTD): Facilitating Mechanistic Understanding of Chemical Effects. ' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Mattingly CJ.' ,'2014-03-23' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database (CTD): Leveraging Species Diversity to Understand Mechanisms of Toxicity.' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Mattingly CJ.' ,'2014-03-23' ,'p' ,NULL ,NULL ) ,( 'BioCreative IV Track 3 CTD: Interoperability and Web Service-based NER' ,'BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.' ,'Wiegers TC' ,'2013-03-08' ,'p' ,NULL ,NULL ) ,( 'BioC for NER Web Services-Based High Level Inter-process Communications' ,'BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.' ,'Wiegers TC' ,'2013-03-07' ,'p' ,NULL ,NULL ) ,( 'Exposure Data Curation for Integration into the Comparative Toxicogenomics Database (CTD). ' ,'Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.' ,'Murphy CG, Mattingly CJ, Davis AP' ,'2013-03-10' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.' ,'Mattingly CJ, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Davis AP.' ,'2013-03-10' ,'p' ,NULL ,NULL ) ,( 'Using CTD to discover and predict molecular connections between environmental chemicals and human health.' ,'Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.' ,'Murphy CG, Davis AP, Saracini-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-03-11' ,'p' ,NULL ,NULL ) ,( 'Predicting Mechanisms of Chemical Toxicity using the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.' ,'Mattingly CJ, Davis AP, Murphy CG, Saraceni Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B.' ,'2012-03-11' ,'p' ,NULL ,NULL ) ,('Collaborative Biocuration--Text Mining Development Task for Document Prioritization for Curation.' ,'BioCreative Workshop 2012. Georgetown University, Washington, DC, USA. Apr 4-5, 2012.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2012-04-04' ,'p' ,NULL ,NULL ) ,('Waiting for a robust Disease Ontology: a merger of OMIM and MeSH as a practical interim solution.' ,'International Conference on Biomedical Ontology, University at Buffalo, NY, USA. Jul 26-30, 2011.' ,'Bello SM, Davis AP, Wiegers TC, Dolan ME, Smith C, Richardson J, Blake J, Eppig JT, Mattingly CJ.' ,'2011-07-26' ,'p' ,NULL ,NULL ) ,('Oracle to PostgreSQL: CTD''s Path to Database Happiness.' ,'Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Jun 8, 2011.' ,'Rosenstein MC, Wiegers TC, McMorran RA.' ,'2011-06-08' ,'p' ,NULL ,NULL ) ,('Environmental chemicals and human health: uncovering the connections with CTD.' ,'Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B, Mattingly CJ.' ,'2011-03-07' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.' ,'Davis AP, Murphy CG, Mattingly CJ.' ,'2011-03-07' ,'p' ,NULL ,NULL ) ,('Using CTD to understand BPA.' ,'NIEHS BPA Grantee Research Update and Coordination Meeting. Research Triangle Park, NC, USA. Sep 21-22, 2010.' ,'Davis AP.' ,'2010-09-21' ,'p' ,NULL ,NULL ) ,('New features at CTD.' ,'The OpenHelix Blog. May 18, 2010.' ,'Davis AP.' ,'2010-05-18' ,'p' ,'http://blog.openhelix.eu/?p=4406' ,NULL ) ,('Use and development of ontologies in the Comparative Toxicogenomics Database (CTD).' ,'Protein Ontology 3rd Annual Meeting. University of Delaware, Newark, DE, USA. Apr 26-27, 2010.' ,'Murphy CG.' ,'2010-04-26' ,'p' ,NULL ,NULL ) ,('CTD: exploring over 1,000,000 chemical-gene-disease interactions.' ,'Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 7-11, 2010.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2010-03-07' ,'p' ,NULL ,NULL ) ,('Mapping OMIM to MeSH: a disease hierarchy for CTD.' ,'Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Feb 23, 2010.' ,'Davis AP.' ,'2010-02-23' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD) Text Mining Study.' ,'3rd International Biocuration Conference. Berlin, Germany. Apr 2009.' ,'Wiegers TC, Murphy C, Saraceni-Richards CA, Rosenstein MC, Davis AP, Mattingly CJ.' ,'2009-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): A discovery tool for identifying chemical-gene-disease networks.' ,'Society of Toxicology Annual Meeting. Baltimore, MD, USA. Mar 2009.' ,'Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.' ,'2009-03-01' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database (CTD) to identify chemical-gene-disease associations.' ,'Society of Experimental Toxicology and Chemistry. Tampa, FL, USA. Nov 2008.' ,'Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.' ,'2008-11-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database.' ,'Annual environmental health sciences core centers meeting. Philadelphia, PA, USA. Oct 2008.' ,'Mattingly CJ.' ,'2008-10-01' ,'p' ,NULL ,NULL ) ,('Using CTD to discover chemical-gene-disease associations: arsenic as a case study.' ,'Mechanisms of Toxicity, Gordon Research Conference, Bates College, Lewiston, ME, USA. Jul 27-Aug 1, 2008.' ,'Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Boyer JL, Mattingly CJ.' ,'2008-07-27' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database (CTD) to Explore Chemical-Gene-Disease Connections.' ,'University of Maine Graduate School of Biomedical Sciences Symposium. Orono, ME, USA. May 2008.' ,'Mattingly CJ.' ,'2008-05-01' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to identify chemical-gene-disease associations: arsenic as a case study.' ,'Society of Toxicology Annual Meeting. Seattle, WA, USA. Mar 2008.' ,'Mattingly CJ, Davis AP, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.' ,'2008-03-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Promoting understanding of chemical-gene-disease associations.' ,'NERC International Collaboration Initiative: Bioinformatics Workshop. Birmingham, UK. Mar 2008.' ,'Mattingly CJ.' ,'2008-03-01' ,'p' ,NULL ,NULL ) ,('Curating the Comparative Toxicogenomics Database: a knowledge and discovery environment for chemical-gene-disease associations.' ,'Second International Biocuration Meeting. San Jose, CA, USA. Oct 2007.' ,'Davis AP, Murphy C, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL, Mattingly CJ.' ,'2007-10-01' ,'p' ,'/documents/davisetal_biocur2007.ppt' ,'/documents/davisetal_biocur2007_abstract.pdf' ) ,('The Comparative Toxicogenomics Database: Promoting Understanding About the Mechanisms of Chemical Actions. Toxicology Division of the American Society for Pharmacology and Experimental Therapeutics (ASPET).' ,'"Toxicogenomics Approaches for Evaluating Drug and Chemical Toxicity" Symposium at the Experimental Biology Annual Meeting. Washington, DC, USA. Apr 2007.' ,'Mattingly CJ.' ,'2007-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database: connecting chemicals, genes, and diseases.' ,'Society of Toxicology Annual Meeting. Charlotte, NC, USA. Mar 2007.' ,'Davis AP, Mattingly CJ, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.' ,'2007-03-01' ,'p' ,'/documents/davisetal_sot2007_poster.pdf' ,'/documents/davisetal_sot2007_abstract.pdf' ) ,('The Comparative Toxicogenomics Database: A Public Resource for Chemical-Gene and Chemical-Protein Interactions.' ,'EPA Science Forum 2006, U.S Environmental Protection Agency, Washington, DC, USA. May 2006.' ,'Davis AP, Mattingly CJ, Rosenstein MC, Forrest JN, Boyer JL.' ,'2006-05-01' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): Promoting Understanding of Chemical-Gene Interactions.' ,'Keystone: the Molecular and Integrative Basis for Toxic Responses. Victoria, BC. May 2006.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Colby GC, Forrest JN, Boyer JL.' ,'2006-05-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 2006.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Forrest JN, Boyer JL.' ,'2006-03-01' ,'p' ,NULL ,NULL ) ,('Data Integration in the Comparative Toxicogenomics Database (CTD).' ,'Annual meeting of the International Society for Computational Biology. Detroit, MI, USA. Jun 2005.' ,'Colby GT, Mattingly CJ, Rosenstein, MC, Forrest JN, Boyer JL.' ,'2005-06-01' ,'p' ,NULL ,NULL ) ,('Cross-Species Comparative Approaches to Understanding Chemical-Gene Interactions.' ,'15th International Conference of Comparative Endocrinology. Boston, MA, USA. May 2005.' ,'Mattingly CJ.' ,'2005-05-01' ,'p' ,NULL ,NULL ) ,('Comparative Approaches to Understanding Gene-Chemical Interactions.' ,'Northland Chapter of the Society of Toxicology Meeting. Minneapolis, MN, USA. Apr 2005.' ,'Mattingly CJ.' ,'2005-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 2005.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2005-03-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Comparative Molecular Approaches to Environmental Health Research.' ,'American Chemical Society National Meeting. Philadelphia, PA, USA. Aug 2004.' ,'Mattingly CJ.' ,'2004-08-01' ,'p' ,NULL ,NULL ) ,('Comparative Approaches to Understanding Mechanisms of Toxicity: CTD.' ,'2004 World Congress on In Vitro Biology. San Francisco, CA, USA. May 2004.' ,'Mattingly CJ.' ,'2004-05-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 2004.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2004-03-01' ,'p' ,NULL ,NULL ) ; -- COMMIT; VACUUM FULL ANALYZE ctd_reference;
Date: 2026-01-23 09:53:25
Statement: /* * Populates the ctd_reference table. * * $Id: pop_ctd_reference.sql 18065 2026-01-23 16:00:46Z twiegers $ */ TRUNCATE TABLE ctd_reference; ALTER SEQUENCE ctd_reference_id_seq RESTART; -- articles INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt -- Is this reference contained in the REFERENCE table? ,is_in_ctd -- Is this reference the one to be used for citing CTD? ,is_primary_citation ,acc_txt ,acc_db_cd ,type_cd ) VALUES ('Integrating AI-powered text mining from PubTator into the manual curation workflow at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2025 Feb 21.' ,'Wiegers TC, Davis AP, Wiegers J, Sciaky D, Barkalow F, Wyatt B, Strong M, McMorran R, Abrar S, Mattingly CJ' ,'2025-02-21' ,false ,FALSE ,'39982792' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database’s 20th anniversary: update 2025.' ,'Nucleic Acids Res. 2024 Oct 10.' ,'Davis AP, Wiegers TC, Sciaky D, Barkalow F, Strong M, Wyatt B, Wiegers J, McMorran R, Abrar S, Mattingly CJ' ,'2024-10-10' ,false ,TRUE ,'39385618' ,'PUBMED' ,'a' ) ,('Transforming environmental health datasets from the comparative toxicogenomics database into chord diagrams to visualize molecular mechanisms.' ,'Front. Toxicol., 21 July 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers J, Abrar S, Sciaky D, Barkalow F, Strong M, Mattingly CJ' ,'2024-07-21' ,false ,FALSE ,'39104826' ,'PUBMED' ,'a' ) ,('CTD Tetramers: a new online tool that computationally links curated chemicals, genes, phenotypes, and diseases to inform molecular mechanisms for environmental health.' ,'Toxicol Sci. 2023 Jul 24:kfad069.' ,'Davis AP, Wiegers TC, Wiegers J, Wyatt B, Johnson RJ, Sciaky D, Barkalow F, Strong M, Planchart A, Mattingly CJ' ,'2023-07-24' ,false ,FALSE ,'37486259' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database (CTD): update 2023.' ,'Nucleic Acids Res. 2022 Sep 28.' ,'Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ' ,'2022-09-28' ,false ,TRUE ,'36169237' ,'PUBMED' ,'a' ) ,('Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the comparative toxicogenomics database.' ,'Curr Res Toxicol.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ' ,'2021-08-05' ,false ,FALSE ,'34458863' ,'PUBMED' ,'a' ) ,('Regulatory Status of Pesticide Residues in Cannabis: Implications to Medical Use in Neurological Diseases.' ,'Curr Res Toxicol. Volume 2, 2021, Pages 140-148.' ,'Pinkhasova DV, Jameson LE, Conrow KD, Simeone MP, Davis AP, Wiegers TC, Mattingly CJ, Leung MCK' ,'2021-07-22' ,false ,FALSE ,'34308371' ,'PUBMED' ,'a' ) ,('CTD anatomy: Analyzing chemical-induced phenotypes and exposures from an anatomical perspective, with implications for environmental health studies.' ,'Curr Res Toxicol. Volume 2, 2021, Pages 128-139.' ,'Davis AP, Wiegers TC, Wiegers J, Grondin CJ, Johnson RJ, Sciaky D, Mattingly CJ' ,'2021-03-06' ,false ,FALSE ,'33768211' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2021.' ,'Nucleic Acids Res. 2020 Oct 17.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Wiegers TC, Mattingly CJ' ,'2020-10-17' ,false ,FALSE ,'33068428' ,'PUBMED' ,'a' ) ,('Leveraging the Comparative Toxicogenomics Database to fill in knowledge gaps for environmental health: a test case for air pollution-induced cardiovascular disease.' ,'Toxicol Sci. 2020 Jul 14.' ,'Davis AP, Wiegers TC, Grondin CJ, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ' ,'2020-07-14' ,false ,FALSE ,'32663284' ,'PUBMED' ,'a' ) ,('Public data sources to support systems toxicology applications.' ,'Curr Opin Toxicol. 2019 August 16:17-24.' ,'Davis AP, Wiegers J, Wiegers TC, Mattingly CJ' ,'2019-08-16' ,false ,FALSE ,'33604492' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2019.' ,'Nucleic Acids Res. 2018 Sep 24.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ' ,'2018-09-24' ,false ,FALSE ,'30247620' ,'PUBMED' ,'a' ) ,('Chemical-induced phenotypes at CTD help inform the pre-disease state and construct adverse outcome pathways.' ,'Toxicol Sci. 2018 May 28.' ,'Davis AP, Wiegers TC, Wiegers J, Johnson RJ, Sciaky D, Grondin CJ, Mattingly CJ' ,'2018-05-28' ,false ,false ,'29846728' ,'PUBMED' ,'a' ) ,('Accessing an Expanded Exposure Science Module at the Comparative Toxicogenomics Database.' ,'Environ Health Perspect. 2018 Jan 18;126(1):014501.' ,'Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ' ,'2018-01-18' ,false ,false ,'29351546' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2017.' ,'Nucleic Acids Res. 2016 Sep 19;[Epub ahead of print]' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, King BL, McMorran R, Wiegers J, Wiegers TC, Mattingly CJ.' ,'2016-10-03' ,false ,FALSE ,'27651457' ,'PUBMED' ,'a' ) ,('Advancing Exposure Science through Chemical Data Curation and Integration in the Comparative Toxicogenomics Database.' ,'Environ Health Perspect. 2016 May 12' ,'Grondin CJ, Davis AP, Wiegers TC, King BL, Wiegers JA, Reif DM, Hoppin JA, Mattingly CJ.' ,'2016-05-12' ,false ,false ,'27170236' ,'PUBMED' ,'a' ) ,('Generating Gene Ontology-Disease Inferences to Explore Mechanisms of Human Disease at the Comparative Toxicogenomics Database.' ,'PLoS One. 2016 May 12;11(5):e0155530.' ,'Davis AP, Wiegers TC, King BL, Wiegers J, Grondin CJ, Sciaky D, Johnson RJ, Mattingly CJ.' ,'2016-05-12' ,false ,false ,'27171405' ,'PUBMED' ,'a' ) ,('ToxEvaluator: an integrated computational platform to aid the interpretation of toxicology study-related findings.' ,'Database (Oxford). 2016 May 9;2016. pii: baw062.' ,'Pelletier D, Wiegers TC, Enayetallah A, Kibbey C, Gosink M, Koza-Taylor P, Mattingly CJ, Lawton M.' ,'2016-05-10' ,false ,false ,'27161010' ,'PUBMED' ,'a' ) ,('Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task.' ,'Database (Oxford). 2016 Mar 19;2016. pii: baw032.' ,'Wei CH, Peng Y, Leaman R, Davis AP, Mattingly CJ, Li J, Wiegers TC, Lu Z.' ,'2016-03-19' ,false ,false ,'26994911' ,'PUBMED' ,'a' ) ,('BioCreative V CDR task corpus: a resource for chemical disease relation extraction.' ,'Database (Oxford). 2016 May 9;2016. pii: baw068' ,'Li J, Sun Y, Johnson RJ, Sciaky D, Wei CH, Leaman R, Davis AP, Mattingly CJ, Wiegers TC, Lu Z.' ,'2016-05-09' ,false ,false ,'27161011' ,'PUBMED' ,'a' ) ,('Laying a Community-Based Foundation for Data-Driven Semantic Standards in Environmental Health Sciences.' ,'Environ Health Perspect. 2016 Feb 12.' ,'Mattingly CJ, Boyles R, Lawler CP, Haugen AC, Dearry A, Haendel M.' ,'2016-02-12' ,false ,false ,'26871594' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database''s 10th year anniversary: update 2015.' ,'Nucleic Acids Res. 2015 Jan;43 (Database issue): D914-20.' ,'Davis AP, Grondin CJ, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Wiegers TC, Mattingly CJ.' ,'2015-01-01' ,false ,FALSE ,'25326323 ' ,'PUBMED' ,'a' ) ,('Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.' ,'Database (Oxford). 2014 Jun 10:bau050.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2014-06-10' ,false ,false ,24919658 ,'PUBMED' ,'a' ) ,('BioC interoperability track overview.' ,'Database (Oxford). 2014 Jun 30:bau053.' ,'Comeau DC, Batista-Navarro RT, Dai HJ, Dogan RI, Yepes AJ, Khare R, Lu Z, Marques H, Mattingly CJ, Neves M, Peng Y, Rak R, Rinaldi F, Tsai RT, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.' ,'2014-06-09' ,false ,false ,24980129 ,'PUBMED' ,'a' ) ,('BioCreative-IV virtual issue.' ,'Database (Oxford). 2014 May 22:bau039.' ,'Arighi CN, Wu CH, Cohen KB, Hirschman L, Krallinger M, Valencia A, Lu Z, Wilbur JW, Wiegers TC' ,'2014-05-22' ,false ,false ,24852177 ,'PUBMED' ,'a' ) ,('A CTD-Pfizer collaboration: manual curation of 88,000 scientific articles text mined for drug-disease and drug-phenotype interactions.' ,'Database (Oxford). 2013 Nov 28:bat080.' ,'Davis AP, Wiegers TC, Roberts PM, King BL, Lay JM, Lennon-Hopkins K, Sciaky D, Johnson R, Keating H, Greene N, Hernandez R, McConnell KJ, Enayetallah AE, Mattingly CJ.' ,'2013-11-28' ,false ,false ,'24288140' ,'PUBMED' ,'a' ) ,('Web services-based text-mining demonstrates broad impacts for interoperability and process simplification.' ,'Proceedings of the Fourth BioCreative Evaluation Workshop 1: 69-84.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2013-10-06' ,false ,false ,NULL ,NULL ,'a' ) ,('BioC: a minimalist approach to interoperability for biomedical text processing.' ,'Database (Oxford). 2013 Sep 18:bat064.' ,'Comeau DC, Islamaj DR, Ciccarese P, Cohen KB, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M, Valencia A, Verspoor K, Wiegers TC, Wu CH, Wilbur WJ.' ,'2013-09-18' ,false ,false ,'24048470' ,'PUBMED' ,'a' ) ,('Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the Comparative Toxicogenomics Database.' ,'PLoS One. 2013 Apr 17;8(4):e58201.' ,'Davis AP, Wiegers TC, Johnson RJ, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, Murphy CG, Mattingly CJ.' ,'2013-04-17' ,false ,false ,'23613709' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2013.' ,'Nucleic Acids Res. 2013 Jan 1;41(D1):D1104-14.' ,'Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2013-01-01' ,false ,FALSE ,'23093600' ,'PUBMED' ,'a' ) ,('Targeted journal curation as a method to improve data currency at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2012 Dec 6;2012:bas051.' ,'Davis AP, Johnson RJ, Lennon-Hopkins K, Sciaky D, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-12-06' ,false ,false ,'23221299' ,'PUBMED' ,'a' ) ,('Collaborative biocuration--text-mining development task for document prioritization for curation.' ,'Database (Oxford). 2012 Nov 22;2012:bas037.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2012-11-22' ,false ,false ,'23180769' ,'PUBMED' ,'a' ) ,('Ranking Transitive Chemical-Disease Inferences Using Local Network Topology in the Comparative Toxicogenomics Database.' ,'PLoS One. 2012;7(11):e46524.' ,'King BL, Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-11-07' ,false ,false ,'23144783' ,'PUBMED' ,'a' ) ,('Text mining for the biocuration workflow.' ,'Database (Oxford). 2012 Apr 18;2012:bas020.' ,'Hirschman L, Burns GA, Krallinger M, Arighi C, Cohen KB, Valencia A, Wu CH, Chatr-Aryamontri A, Dowell KG, Huala E, Lourenço A, Nash R, Veuthey AL, Wiegers T, Winter AG.' ,'2012-04-18' ,false ,false ,'22513129' ,'PUBMED' ,'a' ) ,('MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2012 Mar 20;2012:bar065.' ,'Davis AP, Wiegers TC, Rosenstein MC, Mattingly CJ.' ,'2012-03-20' ,false ,false ,'22434833' ,'PUBMED' ,'a' ) ,('Disease model curation improvements at Mouse Genome Informatics.' ,'Database (Oxford). 2012 Mar 20;2012:bar063.' ,'Bello SM, Richardson JE, Davis AP, Wiegers TC, Mattingly CJ, Dolan ME, Smith CL, Blake JA, Eppig JT.' ,'2012-03-20' ,false ,false ,'22434831' ,'PUBMED' ,'a' ) ,('Providing the Missing Link: the Exposure Science Ontology ExO.' ,'Environ Sci Technol. 2012 Mar 20;46(6):3046-53.' ,'Mattingly CJ, McKone TE, Callahan MA, Blake JA, Cohen Hubal EA.' ,'2012-03-20' ,false ,false ,'22324457' ,'PUBMED' ,'a' ) ,('DiseaseComps: a metric that discovers similar diseases based upon common toxicogenomic profiles at CTD.' ,'Bioinformation. 2011 Oct 14;7(4):154-6.' ,'Davis AP, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2011-10-14' ,false ,false ,'22125387' ,'PUBMED' ,'a' ) ,('The curation paradigm and application tool used for manual curation of the scientific literature at the Comparative Toxicogenomics Database.' ,'Database (Oxford). 2011 Sep 20;2011:bar034.' ,'Davis AP, Wiegers TC, Rosenstein MC, Murphy CG, Mattingly CJ.' ,'2011-09-20' ,false ,false ,'21933848' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: update 2011.' ,'Nucleic Acids Res. 2011 Jan;39(Database issue):D1067-72.' ,'Davis AP, King BL, Mockus S, Murphy CG, Saraceni-Richards C, Rosenstein M, Wiegers T, Mattingly CJ.' ,'2011-01-01' ,false ,false ,'20864448' ,'PUBMED' ,'a' ) ,('GeneComps and ChemComps: a new CTD metric to identify genes and chemicals with shared toxicogenomic profiles.' ,'Bioinformation. 2009 Oct 15;4(4):173-4.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Hampton TH, Mattingly CJ.' ,'2009-10-15' ,false ,false ,'20198196' ,'PUBMED' ,'a' ) ,('Text mining and manual curation of chemical-gene-disease networks for the Comparative Toxicogenomics Database (CTD).' ,'BMC Bioinformatics. 2009 Oct 8;10(1):326.' ,'Wiegers TC, Davis AP, Cohen KB, Hirschman L, Mattingly CJ. ' ,'2009-10-08' ,false ,false ,'19814812' ,'PUBMED' ,'a' ) ,('Genetic and environmental pathways to complex diseases.' ,'BMC Syst Biol. 2009 May 5;3(1):46.' ,'Gohlke JM, Thomas R, Zhang Y, Rosenstein MC, Davis AP, Murphy C, Becker KG, Mattingly CJ, Portier CJ.' ,'2009-05-05' ,false ,false ,'19416532' ,'PUBMED' ,'a' ) ,('Perturbation of defense pathways by low-dose arsenic exposure in zebrafish embryos.' ,'Environ Health Perspect. 2009 Jun;117(6):981-7.' ,'Mattingly CJ, Hampton T, Brothers K, Griffin NE, Planchart AJ.' ,'2009-06-01' ,true ,false ,'19590694' ,'PUBMED' ,'a' ) ,('Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks.' ,'Nucleic Acids Res. 2009 Jan;37(Database issue):D786-92.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ. ' ,'2009-01-01' ,false ,false ,'18782832' ,'PUBMED' ,'a' ) ,('Chemical databases for environmental health and clinical research.' ,'Toxicol Lett. 2009 Apr 10;186(1):62-5.' ,'Mattingly CJ.' ,'2009-04-10' ,false ,false ,'18996453' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database facilitates identification and understanding of chemical-gene-disease associations: arsenic as a case study.' ,'BMC Med Genomics. 2008 Oct 9;1(1):48.' ,'Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2008-10-09' ,false ,false ,'18845002' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies.' ,'J Exp Zoolog A Comp Exp Biol. 2006 Sep 1;305(9):689-92.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2006-09-01' ,false ,false ,'16902965' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database: a cross-species resource for building chemical-gene interaction networks.' ,'Toxicol Sci. 2006 Aug;92(2):587-95.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Colby GT, Forrest JN, Boyer JL.' ,'2006-08-01' ,false ,false ,'16675512' ,'PUBMED' ,'a' ) ,('Promoting comparative molecular studies in environmental health research: an overview of the comparative toxicogenomics database (CTD).' ,'Pharmacogenomics J. 2004;4(1):5-8.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2004-01-01' ,false ,false ,'14735110' ,'PUBMED' ,'a' ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Environ Health Perspect. 2003 May;111(6):793-5.' ,'Mattingly CJ, Colby GT, Forrest JN, Boyer JL.' ,'2003-05-01' ,false ,false ,'12760826' ,'PUBMED' ,'a' ) ; -- Online publications INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt ,type_cd ,url ) VALUES ('Linking chemical data from the Comparative Toxicogenomics Database with adverse outcome pathways from the AOP-Wiki: a mechanistic data-oriented approach to help inform environmental health.' ,'F1000Research 2025, 14:1266 (2025)' ,'Davis AP, Wiegers TC, Sciaky D, Barkalow F, Wyatt B, Wiegers J, McMorran R, Abrar S, Mattingly CJ' ,'2025-11-17' ,'a' ,'https://doi.org/10.12688/f1000research.172567.1' ) ,('Understanding environment-disease connections: An introduction to the Comparative Toxicogenomics Database (CTD).' ,'NCI-Nature Pathway Interaction Database. doi:10.1038/pid.2011.2 (2011).' ,'Mattingly CJ.' ,'2011-06-01' ,'a' ,'' ) ; -- Posters/presentations INSERT INTO ctd_reference (title ,core_citation_txt ,authors_txt ,pub_dt ,type_cd ,url ,abstract_url ) VALUES ('Using the Comparative Toxicogenomics Database (CTD) to explore air pollution-associated adverse pregnancy outcomes by integrating exposure data with toxicological mechanisms.' ,'International Society of Exposure Science. Atlanta, GA. August 17-20, 2025.' ,'Mattingly CJ, Abrar S, Barkalow F, Sciaky D, Wiegers JA, Wyatt B, Wiegers TC, Davis AP.' ,'August 17, 2025' ,'p' ,NULL ,NULL ) ,('Using CTD to provide environmental chemical content and inform adverse outcome pathways from the AOP-Wiki.' ,'2025 EHLC Workshop on AOP Standards. Virtual. June 4-5, 2025.' ,'Davis AP.' ,'June 4, 2025' ,'p' ,NULL ,NULL ) ,('Exploring environmental influences on Alzheimer’s disease using the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Mattingly CJ, Abrar S, Barkalow F, Sciaky D, Strong M, Wiegers JA, Wyatt B, Wiegers TC, Davis AP.' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a resource to distill complex exposure pathways to help inform the environmental health continuum, from populations to molecules.' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Davis AP, Wyatt B, Wiegers TC, Wiegers J, Sciaky D, Barkalaw F, Strong, M, Abrar S, Mattingly CJ.' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to distill exposure information, from molecular mechanisms to populations.' ,'Society of Toxicology 64th Annual Meeting. Orlando, FL, USA. March 16-20, 2025.' ,'Davis AP' ,'March 16, 2025' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a resource to distill complex exposure pathways to help inform the environmental health continuum, from populations to molecules.' ,'International Society of Exposure Science. Montreal, Quebec, Canada. October 20-24, 2024.' ,'Davis AP, Wyatt B, Wiegers TC, Wiegers J, Sciaky D, Barkalaw F, Strong, M, Abrar S, Mattingly CJ.' ,'October 20, 2024' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a public resource to understand the health effects of PFAS.' ,'National PFAS Conference. Ann Arbor, MI, USA. June 10-12, 2024.' ,'Mattingly CJ, Sciaky D, Barkalaw F, Wyatt B, Strong, M, McMorran R, Abrar S, Wiegers J, Wiegers TC, Davis AP.' ,'June 10, 2024' ,'p' ,NULL ,NULL ) ,('CTD Tetramers: filling environmental health knowledge gaps with computed molecular mechanisms.' ,'NIH/NLM/NCBI Journal Club. Virtual. May 22, 2024.' ,'Davis AP.' ,'May 22, 2024' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database: A tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.' ,'Sapporo Exposome. Sopporo, Japan. May 24-27, 2024.' ,'Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP.' ,'May 24, 2024' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD).' ,'NINDS, NIEHS, UDN, and External Experts Environmental Trigger Workshop. Virtual. May 6, 2024.' ,'Mattingly CJ.' ,'May 6, 2024' ,'p' ,NULL ,NULL ) ,('CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.' ,'DRKB Program Network Meeting. Rockville, MD, USA. February 28-29, 2024.' ,'Mattingly CJ, Wyatt B, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Davis AP' ,'February 28, 2024' ,'p' ,NULL ,NULL ) ,('CTD’s 20th anniversary: providing curated data for environmental health, from molecules to populations.' ,'Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.' ,'Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Wyatt B, Abrat S, Mattingly CJ.' ,'March 10, 2024' ,'p' ,NULL ,NULL ) ,('Surveying environmental influences for Alzheimer disease using the public Comparative Toxicogenomics Database.' ,'Society of Toxicology 63rd Annual Meeting. Salt Lake City, UT, USA. March 10-14, 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.' ,'March 10, 2024' ,'p' ,NULL ,NULL ) ,('CTD integrates curated chemical, gene, phenotype, anatomy, disease, and exposure data to fill knowledge gaps for environmental health: PFAS-childhood asthma as a use case.' ,'USA Exposome Symposium: Children’s Health, Environmental Justice, and the Exposome. Nashville, TN, USA. January 22-24, 2024.' ,'Wyatt B, Davis AP, Wiegers TC, Wiegers JA, Sciaky D, Barkalow F, Strong M, Abrat S, Mattingly CJ.' ,'January 22, 2024' ,'p' ,NULL ,NULL ) ,('Using CTD to fill knowledge gaps for environmental neuroscience.' ,'NIH Environmental Neuroscience Working Group. Virtual. August 29 2023.' ,'Davis AP.' ,'August 29 2023' ,'p' ,NULL ,NULL ) ,('Using CTD to fill knowledge gaps for environmental health.' ,'Jonathan Hamm Lab Seizure Project Meeting. Virtual. December 15, 2023.' ,'Davis AP.' ,'December 15, 2023' ,'p' ,NULL ,NULL ) ,('CTD Tetramers: a new online tool to fill knowledge gaps about environmental health.' ,'Society of Toxicology 62nd Annual Meeting. Nashville, TN, USA. March 19-23, 2023.' ,'Mattingly CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 19, 2023' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database: a tool to investigate the effects of environmental exposures on the etiology of Alzheimer’s disease.' ,'Alzheimer’s Association International Conference. Amsterdam, Netherlands. July 16-20, 2023.' ,'Mattingly CJ, Wiegers TC, Wiegers JA, Sciaky D, Johnson RJ, Davis AP. ' ,'July 16, 2023' ,'p' ,NULL ,NULL ) ,('Introduction to CTD: navigating curated data t fill in knowledge gaps for environmental health.' ,'The Jackson Laboratory. Bar Harbor, ME, USA. July 12, 2022' ,'Davis AP.' ,'July 12, 2022' ,'p' ,NULL ,NULL ) ,('CTD: integrating chemical, gene, phenotype, anatomy, disease, and exposure data to fill in knowledge gaps for environmental health' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Davis AP, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Analyzing e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database.' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Davis AP, Grondin CJ, Wiegers JA, Wiegers TC, Sciaky D, Johnson RJ, Mattingly CJ.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Mechanism of neurological hazards from insecticide exposure in cannabis.' ,'Society of Toxicology 61st Annual Meeting. San Diego, CA, USA. March 28-31, 2022.' ,'Jameson L, Rivera A, Conrow K, Pinkhasova D, Jourachian N, Johnson S, Davis AP, Wiegers T, Sammi S, Mattingly CJ, Afia I, Orser C, Cannon J, Leung M.' ,'March 28, 2022' ,'p' ,NULL ,NULL ) ,('Leveraging CTD data to fill in knowledge gaps for environmental health.' ,'OpenTox Euro. Virtual. September 24, 2021.' ,'Davis AP.' ,'September 24, 2021' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): linking chemicals, genes, phenotypes, diseases, and exposures to fill in knowledge gaps for environmental health.' ,'Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 12, 2021' ,'p' ,NULL ,NULL ) ,('Regulatory status of pesticide residues I cannabis: implications to medical use in neurological diseases.' ,'Society of Toxicology 60th Annual Meeting. Virtual. March 12-16, 2021.' ,'Pinkhasova S, Jameson L, Conrow K, Simeone M, Davis AP, Wiegers T, Mattingly CJ, Leung M.' ,'March 12, 2021' ,'p' ,NULL ,NULL ) ,('Analyzing the Effects of Emerging Environmental Exposures on Human Health Using the Comparative Toxicogenomics Database.' ,'International Society of Exposure Science. Virtual. August 30-September 2, 2021.' ,'Grondin C, Davis AP, Johnson R, Sciaky D, Wiegers J, Wiegers T, Mattingly CJ. ' ,'August 30, 2021' ,'p' ,NULL ,NULL ) ,('Introduction to CTD.' ,'Arizona State University. Virtual. March 18, 2021.' ,'Davis AP.' ,'March 18, 2021' ,'p' ,NULL ,NULL ) ,('Leveraging CTD to fill in knowledge gaps for environmental health science.' ,'NTP Data Science Seminar Series. Virtual. June 19, 2021.' ,'Davis AP.' ,'June 19, 2021' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): a comprehensive view of chemical exposures, mechanisms, and biological effects.' ,'Society of Toxicology 59th Annual Meeting. Virtual. March 15-19, 2020.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 15, 2020' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): mechanism meets exposure science illustrated through a bisphenol A-diabetes case study.' ,'Society of Toxicology 58th Annual Meeting. Baltimore, MD, USA. March 11-14, 2019.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP. ' ,'March 11, 2019' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to further our understanding of environmental exposures on human health.' ,'International Society of Exposure Science. Ottawa, Canada. August 27-29, 2018.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Johnson RJ, Sciaky D, Mattingly CJ. ' ,'August 27, 2018' ,'p' ,NULL ,NULL ) ,('Chemical-induced phenotypes at CTD: informing the pre-disease state and adverse outcome pathways.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Mattingly CJ. ' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): an integrated resource for chemical, gene, phenotype, and exposure data.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Facilitating exposure data analysis in the Comparative Toxicogenomics Database: a case study of heavy metals and metabolic syndrome.' ,'Society of Toxicology 57th Annual Meeting. San Antonio, TX, USA. March 11-15, 2018.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Green A, Planchart A, Mattingly CJ.' ,'March 11, 2018' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): integrating chemical, gene, phenotype, disease, and exposure science data.' ,'Society of Toxicology 56th Annual Meeting. Baltimore, MD, USA. March 12-16, 2017.' ,'Mattingly CJ, Grondin CJ, Johnson RJ, Sciaky D, Wiegers JA, Wiegers TC, Davis AP.' ,'March 12, 2017' ,'p' ,NULL ,NULL ) ,('Chemical-phenotype curation at the Comparative Toxicogenomics Database.' ,'10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.' ,'Davis AP, Johnson RJ, Sciaky D, Grondin CJ, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'March 26, 2017' ,'p' ,NULL ,NULL ) ,('Exposure science in CTD: linking chemical stressors to outcomes via an Exposure Ontology.' ,'10th International Biocuration Conference. Palo Alto, CA, USA. March 26-29, 2017.' ,'Grondin CJ, Davis AP, Wiegers J, Wiegers, TC, King BL, Mattingly CJ.' ,'March 26, 2017' ,'p' ,NULL ,NULL ) ,('Curation and integration of exposure science at the Comparative Toxicogenomics Database: an introduction for new users.' ,'Emory Exposome Summer Course. Atlanta, GA, USA. June 13-15, 2016.' ,'Davis AP.' ,'June 13, 2016' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Expanding Exposome and Phenotype Content to Elucidate Chemical-Disease Relationships.' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.' ,'Mattingly CJ, Grondin CJ, Johnson R, Sciaky D, King BL, Wiegers JA, Wiegers TC, Davis AP.' ,'2016-03-18' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Advancing understanding of molecular connections among chemicals, genes and diseases.' ,'American Chemical Society National Meeting. San Diego, CA, USA Mar 13-17, 2016.' ,'Grondin CJ, Davis AP, Wiegers TC, Wiegers JA, Mattingly CJ.' ,'2016-03-17' ,'p' ,NULL ,NULL ) ,('Elucidating Correlations between High-Throughput Chemical Screening and Curated Literature.' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 13-17, 2016.' ,'Collier G, Planchart A, Reif DM, Mattingly CJ.' ,'2016-03-16' ,'p' ,NULL ,NULL ) ,('BioCreative V Track 3: Chemical-Disease Relation AND Disease Named Entity Recognition and Normalization.' ,'BioCreative V Challenge Workshop. cicCartuja, Sevilla, Spain. Sept 9-11, 2015.' ,'Wiegers TC, Lu, Z.' ,'2015-09-10' ,'p' ,NULL ,NULL ) ,( 'Exposure Science Data and the Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.' ,'Grondin CJ, Davis AP, Wiegers JA, Wiegers TC, Mattingly CJ.' ,'2015-03-22' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database: Ten Years in the Making.' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 22-26, 2015.' ,'Mattingly CJ, Grondin CJ, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, Wiegers JA, McMorran R, King BL, Wiegers TC, Davis AP.' ,'2015-03-22' ,'p' ,NULL ,NULL ) ,( 'Exposure data and the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Grondin CJ, Davis AP, Mattingly CJ.' ,'2014-03-25' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Davis AP, Mattingly CJ, Murphy CG, Lay JM, Lennon-Hopkins K, Sciaky D, Saracini-Richards C, King BL, Rosenstein MC, Wiegers TC.' ,'2014-03-24' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database (CTD): Facilitating Mechanistic Understanding of Chemical Effects. ' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Mattingly CJ.' ,'2014-03-23' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database (CTD): Leveraging Species Diversity to Understand Mechanisms of Toxicity.' ,'Society of Toxicology Annual Meeting. Phoenix, AZ, USA. Mar 23-27, 2014.' ,'Mattingly CJ.' ,'2014-03-23' ,'p' ,NULL ,NULL ) ,( 'BioCreative IV Track 3 CTD: Interoperability and Web Service-based NER' ,'BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.' ,'Wiegers TC' ,'2013-03-08' ,'p' ,NULL ,NULL ) ,( 'BioC for NER Web Services-Based High Level Inter-process Communications' ,'BioCreative IV Conference. Bethesda, MD, USA. Oct 7-9, 2013.' ,'Wiegers TC' ,'2013-03-07' ,'p' ,NULL ,NULL ) ,( 'Exposure Data Curation for Integration into the Comparative Toxicogenomics Database (CTD). ' ,'Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.' ,'Murphy CG, Mattingly CJ, Davis AP' ,'2013-03-10' ,'p' ,NULL ,NULL ) ,( 'The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. San Antonio, TX, USA. Mar 10-14, 2013.' ,'Mattingly CJ, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saracini-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Davis AP.' ,'2013-03-10' ,'p' ,NULL ,NULL ) ,( 'Using CTD to discover and predict molecular connections between environmental chemicals and human health.' ,'Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.' ,'Murphy CG, Davis AP, Saracini-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2012-03-11' ,'p' ,NULL ,NULL ) ,( 'Predicting Mechanisms of Chemical Toxicity using the Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. San Francisco. CA, USA. Mar 11-15, 2012.' ,'Mattingly CJ, Davis AP, Murphy CG, Saraceni Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B.' ,'2012-03-11' ,'p' ,NULL ,NULL ) ,('Collaborative Biocuration--Text Mining Development Task for Document Prioritization for Curation.' ,'BioCreative Workshop 2012. Georgetown University, Washington, DC, USA. Apr 4-5, 2012.' ,'Wiegers TC, Davis AP, Mattingly CJ.' ,'2012-04-04' ,'p' ,NULL ,NULL ) ,('Waiting for a robust Disease Ontology: a merger of OMIM and MeSH as a practical interim solution.' ,'International Conference on Biomedical Ontology, University at Buffalo, NY, USA. Jul 26-30, 2011.' ,'Bello SM, Davis AP, Wiegers TC, Dolan ME, Smith C, Richardson J, Blake J, Eppig JT, Mattingly CJ.' ,'2011-07-26' ,'p' ,NULL ,NULL ) ,('Oracle to PostgreSQL: CTD''s Path to Database Happiness.' ,'Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Jun 8, 2011.' ,'Rosenstein MC, Wiegers TC, McMorran RA.' ,'2011-06-08' ,'p' ,NULL ,NULL ) ,('Environmental chemicals and human health: uncovering the connections with CTD.' ,'Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Mockus S, Rosenstein MC, Wiegers TC, King B, Mattingly CJ.' ,'2011-03-07' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database.' ,'Society of Toxicology Annual Meeting. Washington, DC, USA. Mar 7-10, 2011.' ,'Davis AP, Murphy CG, Mattingly CJ.' ,'2011-03-07' ,'p' ,NULL ,NULL ) ,('Using CTD to understand BPA.' ,'NIEHS BPA Grantee Research Update and Coordination Meeting. Research Triangle Park, NC, USA. Sep 21-22, 2010.' ,'Davis AP.' ,'2010-09-21' ,'p' ,NULL ,NULL ) ,('New features at CTD.' ,'The OpenHelix Blog. May 18, 2010.' ,'Davis AP.' ,'2010-05-18' ,'p' ,'http://blog.openhelix.eu/?p=4406' ,NULL ) ,('Use and development of ontologies in the Comparative Toxicogenomics Database (CTD).' ,'Protein Ontology 3rd Annual Meeting. University of Delaware, Newark, DE, USA. Apr 26-27, 2010.' ,'Murphy CG.' ,'2010-04-26' ,'p' ,NULL ,NULL ) ,('CTD: exploring over 1,000,000 chemical-gene-disease interactions.' ,'Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 7-11, 2010.' ,'Davis AP, Murphy CG, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Mattingly CJ.' ,'2010-03-07' ,'p' ,NULL ,NULL ) ,('Mapping OMIM to MeSH: a disease hierarchy for CTD.' ,'Mouse Genome Informatics Group Meeting. The Jackson Laboratory. Bar Harbor, ME, USA. Feb 23, 2010.' ,'Davis AP.' ,'2010-02-23' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD) Text Mining Study.' ,'3rd International Biocuration Conference. Berlin, Germany. Apr 2009.' ,'Wiegers TC, Murphy C, Saraceni-Richards CA, Rosenstein MC, Davis AP, Mattingly CJ.' ,'2009-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): A discovery tool for identifying chemical-gene-disease networks.' ,'Society of Toxicology Annual Meeting. Baltimore, MD, USA. Mar 2009.' ,'Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.' ,'2009-03-01' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database (CTD) to identify chemical-gene-disease associations.' ,'Society of Experimental Toxicology and Chemistry. Tampa, FL, USA. Nov 2008.' ,'Mattingly CJ, Murphy C, Saraceni-Richards CA, Rosenstein MC, Wiegers TC, Davis AP.' ,'2008-11-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database.' ,'Annual environmental health sciences core centers meeting. Philadelphia, PA, USA. Oct 2008.' ,'Mattingly CJ.' ,'2008-10-01' ,'p' ,NULL ,NULL ) ,('Using CTD to discover chemical-gene-disease associations: arsenic as a case study.' ,'Mechanisms of Toxicity, Gordon Research Conference, Bates College, Lewiston, ME, USA. Jul 27-Aug 1, 2008.' ,'Davis AP, Murphy CG, Rosenstein MC, Wiegers TC, Boyer JL, Mattingly CJ.' ,'2008-07-27' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database (CTD) to Explore Chemical-Gene-Disease Connections.' ,'University of Maine Graduate School of Biomedical Sciences Symposium. Orono, ME, USA. May 2008.' ,'Mattingly CJ.' ,'2008-05-01' ,'p' ,NULL ,NULL ) ,('Using the Comparative Toxicogenomics Database to identify chemical-gene-disease associations: arsenic as a case study.' ,'Society of Toxicology Annual Meeting. Seattle, WA, USA. Mar 2008.' ,'Mattingly CJ, Davis AP, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.' ,'2008-03-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Promoting understanding of chemical-gene-disease associations.' ,'NERC International Collaboration Initiative: Bioinformatics Workshop. Birmingham, UK. Mar 2008.' ,'Mattingly CJ.' ,'2008-03-01' ,'p' ,NULL ,NULL ) ,('Curating the Comparative Toxicogenomics Database: a knowledge and discovery environment for chemical-gene-disease associations.' ,'Second International Biocuration Meeting. San Jose, CA, USA. Oct 2007.' ,'Davis AP, Murphy C, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL, Mattingly CJ.' ,'2007-10-01' ,'p' ,'/documents/davisetal_biocur2007.ppt' ,'/documents/davisetal_biocur2007_abstract.pdf' ) ,('The Comparative Toxicogenomics Database: Promoting Understanding About the Mechanisms of Chemical Actions. Toxicology Division of the American Society for Pharmacology and Experimental Therapeutics (ASPET).' ,'"Toxicogenomics Approaches for Evaluating Drug and Chemical Toxicity" Symposium at the Experimental Biology Annual Meeting. Washington, DC, USA. Apr 2007.' ,'Mattingly CJ.' ,'2007-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database: connecting chemicals, genes, and diseases.' ,'Society of Toxicology Annual Meeting. Charlotte, NC, USA. Mar 2007.' ,'Davis AP, Mattingly CJ, Rosenstein MC, Wiegers T, Forrest JN, Boyer JL.' ,'2007-03-01' ,'p' ,'/documents/davisetal_sot2007_poster.pdf' ,'/documents/davisetal_sot2007_abstract.pdf' ) ,('The Comparative Toxicogenomics Database: A Public Resource for Chemical-Gene and Chemical-Protein Interactions.' ,'EPA Science Forum 2006, U.S Environmental Protection Agency, Washington, DC, USA. May 2006.' ,'Davis AP, Mattingly CJ, Rosenstein MC, Forrest JN, Boyer JL.' ,'2006-05-01' ,'p' ,NULL ,NULL ) ,('Comparative Toxicogenomics Database (CTD): Promoting Understanding of Chemical-Gene Interactions.' ,'Keystone: the Molecular and Integrative Basis for Toxic Responses. Victoria, BC. May 2006.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Colby GC, Forrest JN, Boyer JL.' ,'2006-05-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. San Diego, CA, USA. Mar 2006.' ,'Mattingly CJ, Rosenstein MC, Davis AP, Forrest JN, Boyer JL.' ,'2006-03-01' ,'p' ,NULL ,NULL ) ,('Data Integration in the Comparative Toxicogenomics Database (CTD).' ,'Annual meeting of the International Society for Computational Biology. Detroit, MI, USA. Jun 2005.' ,'Colby GT, Mattingly CJ, Rosenstein, MC, Forrest JN, Boyer JL.' ,'2005-06-01' ,'p' ,NULL ,NULL ) ,('Cross-Species Comparative Approaches to Understanding Chemical-Gene Interactions.' ,'15th International Conference of Comparative Endocrinology. Boston, MA, USA. May 2005.' ,'Mattingly CJ.' ,'2005-05-01' ,'p' ,NULL ,NULL ) ,('Comparative Approaches to Understanding Gene-Chemical Interactions.' ,'Northland Chapter of the Society of Toxicology Meeting. Minneapolis, MN, USA. Apr 2005.' ,'Mattingly CJ.' ,'2005-04-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. New Orleans, LA, USA. Mar 2005.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2005-03-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD): Comparative Molecular Approaches to Environmental Health Research.' ,'American Chemical Society National Meeting. Philadelphia, PA, USA. Aug 2004.' ,'Mattingly CJ.' ,'2004-08-01' ,'p' ,NULL ,NULL ) ,('Comparative Approaches to Understanding Mechanisms of Toxicity: CTD.' ,'2004 World Congress on In Vitro Biology. San Francisco, CA, USA. May 2004.' ,'Mattingly CJ.' ,'2004-05-01' ,'p' ,NULL ,NULL ) ,('The Comparative Toxicogenomics Database (CTD).' ,'Society of Toxicology Annual Meeting. Salt Lake City, UT, USA. Mar 2004.' ,'Mattingly CJ, Colby GT, Rosenstein MC, Forrest JN, Boyer JL.' ,'2004-03-01' ,'p' ,NULL ,NULL ) ; -- COMMIT; VACUUM FULL ANALYZE ctd_reference;
Date: 2026-01-23 11:13:45
12 1 LOG: database system was interrupted; last known up at ...
Times Reported Most Frequent Error / Event #12
Day Hour Count Jan 18 15 1 13 1 ERROR: permission denied for table ...
Times Reported Most Frequent Error / Event #13
Day Hour Count Jan 23 13 1 - ERROR: permission denied for table data_load
Statement: insert into load.DATA_LOAD( id,db_id,release_tm,release_nm,load_start_tm, status_txt ) values ( 30 ,21 ,'Fri Jan 23 13:09:08 EST 2026' ,null ,'Fri Jan 23 13:09:08 EST 2026' ,'OK')
Date: 2026-01-23 13:09:08 Database: ctddev51 Application: User: edit Remote:
14 1 ERROR: invalid reference to FROM-clause entry for table "..."
Times Reported Most Frequent Error / Event #14
Day Hour Count Jan 21 16 1 - ERROR: invalid reference to FROM-clause entry for table "cc" at character 712
Hint: There is an entry for table "cc", but it cannot be referenced from this part of the query.
Statement: select count( distinct (reference_acc_txt ,reference_acc_db_id ,chem_acc_txt ,chem_acc_db_id ,chem_nm ,chem_nm_html ,chem_conc ,chem_conc_range ,taxon_acc_txt ,taxon_acc_db_id ,taxon_nm ,taxon_nm_html ,disease_acc_txt ,disease_acc_db_id ,disease_nm ,disease_nm_html ,chem_conc_exp_route_nm ,ixn_qualifier_nm ,note ,action_type_cd ,chem_co_nm ,chem_catalog_nbr ,cca.anatomy_acc_txt ) ) from pub2.chem_conc cc ,pub2.chem_conc_anatomy cca where cc.cc.id = cca.chem_conc_idDate: 2026-01-21 16:52:42
15 1 ERROR: cannot drop table ... because other objects depend on it
Times Reported Most Frequent Error / Event #15
Day Hour Count Jan 22 15 1 - ERROR: cannot drop table chem_conc because other objects depend on it
Detail: constraint chem_conc_chem_conc_anatomy_fk on table chem_conc_anatomy depends on table chem_conc
Hint: Use DROP ... CASCADE to drop the dependent objects too.
Statement: DROP TABLE IF EXISTS chem_conc ;Date: 2026-01-22 15:43:00
16 1 WARNING: there is no transaction in progress
Times Reported Most Frequent Error / Event #16
Day Hour Count Jan 23 10 1