Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,143

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

The CompTox Chemistry Dashboard: a community data resource for environmental chemistry

Open access
Williams, Antony J., Grulke, Christopher M., Edwards, Jeff, McEachran, Andrew D., Mansouri, Kamel, Baker, Nancy C., Patlewicz, Grace, Shah, Imran, Wambaugh, John F., Judson, Richard S., Richard, Ann M.·2017·Journal of Cheminformatics

Abstract

Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protection Agency's (EPA) web-based CompTox Chemistry Dashboard is addressing these needs by integrating diverse types of relevant domain data through a cheminformatics layer, built upon a database of curated substances linked to chemical structures. These data include physicochemical, environmental fate and transport, exposure, usage, in vivo toxicity, and in vitro bioassay data, surfaced through an integration hub with link-outs to additional EPA data and public domain online resources. Batch searching allows for direct chemical identifier (ID) mapping and downloading of multiple data streams in several different formats. This facilitates fast access to available structure, property, toxicity, and bioassay data for collections of chemicals (hundreds to thousands at a time). Advanced search capabilities are available to support, for example, non-targeted analysis and identification of chemicals using mass spectrometry. The contents of the chemistry database, presently containing ~ 760,000 substances, are available as public domain data for download. The chemistry content underpinning the Dashboard has been aggregated over the past 15 years by both manual and auto-curation techniques within EPA's DSSTox project. DSSTox chemical content is subject to strict quality controls to enforce consistency among chemical substance-structure identifiers, as well as list curation review to ensure accurate linkages of DSSTox substances to chemical lists and associated data. The Dashboard, publicly launched in April 2016, has expanded considerably in content and user traffic over the past year. It is continuously evolving with the growth of DSSTox into high-interest or data-rich domains of interest to EPA, such as chemicals on the Toxic Substances Control Act listing, while providing the user community with a flexible and dynamic web-based platform for integration, processing, visualization and delivery of data and resources. The Dashboard provides support for a broad array of research and regulatory programs across the worldwide community of toxicologists and environmental scientists.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s13321-017-0247-6

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Research works printed but not linked: 54

  1. Galperin MY, Fernández-Suárez XM, Rigden DJ (2017) The 24th annual Nucleic Acids Research database issue: a look back and upcoming changes. Nucleic Acids Res 45(D1):D1–D11. https://doi.org/10.1093/nar/gkw1188 · DOI
  2. PubChem. https://pubchem.ncbi.nlm.nih.gov/ . Accessed 19 Sept 2017
  3. Bento AP, Gaulton A, Hersey A, Bellis LJ, Chambers J, Davies M, Krüger FA, Light Y, Mak L, McGlinchey S, Nowotka M, Papadatos G, Santos R, Overington JP (2014) The ChEMBL bioactivity database: an update. Nucleic Acids Res 42(D1):D1083–D1090. https://doi.org/10.1093/nar/gkt1031 · DOI · Paper page
  4. Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, Fung C, Nikolai L, Lewis M, Coutouly MA, Forsythe I, Tang P, Shrivastava S, Jeroncic K, Stothard P, Amegbey G, Block D, Hau DD, Wagner J, Miniaci J, Clements M, Gebremedhin M, Guo N, Zhang Y, Duggan GE, MacInnis GD, Weljie AM, Dowlatabadi R, Bamforth F, Clive D, Greiner R, Li L, Marrie T, Sykes BD, Vogel HJ, Querengesser L (2007) HMDB: the Human Metabolome Database. Nucleic Acids Res 35(Database):D521–D526. https://doi.org/10.1093/nar/gkl923 · DOI · Paper page
  5. Dix DJ, Houck KA, Martin MT, Richard AM, Setzer RW, Kavlock RJ (2007) The ToxCast program for prioritizing toxicity testing of environmental chemicals. Toxicol Sci 95(1):5–12. https://doi.org/10.1093/toxsci/kfl103 · DOI · Paper page
  6. Dionisio KL, Frame AM, Goldsmith M-R, Wambaugh JF, Liddell A, Cathey T, Smith D, Vail J, Ernstoff AS, Fantke P, Jolliet O, Judson RS (2015) Exploring consumer exposure pathways and patterns of use for chemicals in the environment. Toxicol Rep 2:228–237. https://doi.org/10.1016/j.toxrep.2014.12.009 · DOI
  7. Goldsmith MR, Grulke CM, Brooks RD, Transue TR, Tan YM, Frame A, Egeghy PP, Edwards R, Chang DT, Tornero-Velez R, Isaacs K, Wang A, Johnson J, Holm K, Reich M, Mitchell J, Vallero DA, Phillips L, Phillips M, Wambaugh JF, Judson RS, Buckley TJ, Dary CC (2014) Development of a consumer product ingredient database for chemical exposure screening and prioritization. Food Chem Toxicol 65:269–279. https://doi.org/10.1016/j.fct.2013.12.029 · DOI
  8. Wambaugh JF, Setzer RW, Reif DM, Gangwal S, Mitchell-Blackwood J, Arnot JA, Joliet O, Frame A, Rabinowitz J, Knudsen TB, Judson RS, Egeghy P, Vallero D, Cohen Hubal EA (2013) High-throughput models for exposure-based chemical prioritization in the ExpoCast project. Environ Sci Technol 47(15):8479–8488. https://doi.org/10.1021/es400482g · DOI · Paper page
  9. Isaacs KK, Glen WG, Egeghy P, Goldsmith MR, Smith L, Vallero D, Brooks R, Grulke CM, Ozkaynak H (2014) SHEDS-HT: an integrated probabilistic exposure model for prioritizing exposures to chemicals with near-field and dietary sources. Environ Sci Technol 48(21):12750–12759. https://doi.org/10.1021/es502513w · DOI
  10. Mansouri K, Grulke CM, Richard AM, Judson RS, Williams AJ (2016) An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modelling$. SAR QSAR Environ Res 27(11):911–937. https://doi.org/10.1080/1062936x.2016.1253611 · DOI
  11. Mansouri K, Grulke CM, Judson RS, Williams AJ (2017) OPERA: a free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints (to be submitted for publication to Journal of Cheminformatics) · DOI · Paper page
  12. Judson R, Richard A, Dix D, Houck K, Elloumi F, Martin M, Cathey T, Transue TR, Spencer R, Wolf M (2008) ACToR—aggregated computational toxicology resource. Toxicol Appl Pharmacol 233(1):7–13. https://doi.org/10.1016/j.taap.2007.12.037 · DOI · Paper page
  13. Kavlock R, Chandler K, Houck K, Hunter S, Judson R, Kleinstreuer N, Knudsen T, Martin M, Padilla S, Reif D, Richard A, Rotroff D, Sipes N, Dix D (2012) Update on EPA’s ToxCast program: providing high throughput decision support tools for chemical risk management. Chem Res Toxicol 25(7):1287–1302. https://doi.org/10.1021/tx3000939 · DOI · Paper page
  14. Tice RR, Austin CP, Kavlock RJ, Bucher JR (2013) Improving the human hazard characterization of chemicals: a Tox21 update. Environ Health Perspect 121(7):756–765. https://doi.org/10.1289/ehp.1205784 · DOI · Paper page
  15. Wambaugh JF, Wetmore BA, Pearce R, Strope C, Goldsmith R, Sluka JP, Sedykh A, Tropsha A, Bosgra S, Shah I, Judson R, Thomas RS, Setzer RW (2015) Toxicokinetic triage for environmental chemicals. Toxicol Sci. https://doi.org/10.1093/toxsci/kfv118 · DOI
  16. Ring CL, Pearce RG, Setzer RW, Wetmore BA, Wambaugh JF (2017) Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability. Environ Int 106:105–118. https://doi.org/10.1016/j.envint.2017.06.004 · DOI
  17. Wambaugh JF, Wang A, Dionisio KL, Frame A, Egeghy P, Judson R, Setzer RW (2014) High throughput heuristics for prioritizing human exposure to environmental chemicals. Environ Sci Technol 48(21):12760–12767. https://doi.org/10.1021/es503583j · DOI · Paper page
  18. Richard AM (2004) DSSTox Website launch: improving public access to databases for building structure-toxicity prediction models. Preclinica 2:103–108
  19. Richard AM, Gold LS, Nicklaus MC (2006) Chemical structure indexing of toxicity data on the internet: moving toward a flat world. Curr Opin Drug Discov Devel 9(3):314–325
  20. Richard AM, Judson RS, Houck KA, Grulke CM, Volarath P, Thillainadarajah I, Yang C, Rathman J, Martin MT, Wambaugh JF, Knudsen TB, Kancherla J, Mansouri K, Patlewicz G, Williams AJ, Little SB, Crofton KM, Thomas RS (2016) ToxCast chemical landscape: paving the road to 21st century toxicology. Chem Res Toxicol 29(8):1225–1251. https://doi.org/10.1021/acs.chemrestox.6b00135 · DOI · Paper page
  21. Williams AJ, Ekins S, Tkachenko V (2012) Towards a gold standard: regarding quality in public domain chemistry databases and approaches to improving the situation. Drug Discov Today 17(13–14):685–701. https://doi.org/10.1016/j.drudis.2012.02.013 · DOI
  22. Williams AJ, Ekins S (2011) A quality alert and call for improved curation of public chemistry databases. Drug Discov Today 16(17–18):747–750. https://doi.org/10.1016/j.drudis.2011.07.007 · DOI
  23. Richard AM, Williams CR (2002) Distributed structure-searchable toxicity (DSSTox) public database network: a proposal. Mutat Res 499(1):27–52 · DOI · Paper page
  24. Judson RS, Houck KA, Kavlock RJ, Knudsen TB, Martin MT, Mortensen HM, Reif DM, Rotroff DM, Shah I, Richard AM, Dix DJ (2010) In vitro screening of environmental chemicals for targeted testing prioritization: the ToxCast project. Environ Health Perspect 118(4):485–492. https://doi.org/10.1289/ehp.0901392 · DOI · Paper page
  25. Filer DL, Kothiya P, Setzer RW, Judson RS, Martin MT (2016) tcpl: the ToxCast pipeline for high-throughput screening data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btw680 · DOI · Paper page
  26. Judson RS, Martin MT, Egeghy P, Gangwal S, Reif DM, Kothiya P, Wolf M, Cathey T, Transue T, Smith D, Vail J, Frame A, Mosher S, Cohen Hubal EA, Richard AM (2012) Aggregating Data for Computational Toxicology Applications: the U.S. Environmental Protection Agency (EPA) Aggregated Computational Toxicology Resource (ACToR) System. Int J Mol Sci 13(2):1805–1831. https://doi.org/10.3390/ijms13021805 · DOI
  27. Isaacs KK, Goldsmith M-R, Egeghy P, Phillips K, Brooks R, Hong T, Wambaugh JF (2016) Characterization and prediction of chemical functions and weight fractions in consumer products. Toxicol Rep 3:723–732. https://doi.org/10.1016/j.toxrep.2016.08.011 · DOI
  28. Phillips KA, Wambaugh JF, Grulke CM, Dionisio KL, Isaacs KK (2017) High-throughput screening of chemicals as functional substitutes using structure-based classification models. Green Chem 19(4):1063–1074. https://doi.org/10.1039/c6gc02744j · DOI
  29. Dionisio KL, Phillips KA, Price PS, Grulke CM, Williams AJ, Biryol D, Hong T, Isaacs KK (2017) The Chemical and Products Database, a resource for exposure-relevant data on chemicals in consumer products. Nat Sci Data (submitted for publication) · DOI · Paper page
  30. Braekevelt E, Tittlemier SA, Tomy GT (2003) Direct measurement of octanol–water partition coefficients of some environmentally relevant brominated diphenyl ether congeners. Chemosphere 51(7):563–567. https://doi.org/10.1016/s0045-6535(02)00841-x · DOI · Paper page
  31. Zang Q, Mansouri K, Williams AJ, Judson RS, Allen DG, Casey WM, Kleinstreuer NC (2017) In silico prediction of physicochemical properties of environmental chemicals using molecular fingerprints and machine learning. J Chem Inf Model 57(1):36–49. https://doi.org/10.1021/acs.jcim.6b00625 · DOI · Paper page
  32. Wetmore BA, Wambaugh JF, Ferguson SS, Sochaski MA, Rotroff DM, Freeman K, Clewell HJ 3rd, Dix DJ, Andersen ME, Houck KA, Allen B, Judson RS, Singh R, Kavlock RJ, Richard AM, Thomas RS (2012) Integration of dosimetry, exposure, and high-throughput screening data in chemical toxicity assessment. Toxicol Sci 125(1):157–174. https://doi.org/10.1093/toxsci/kfr254 · DOI · Paper page
  33. Gülden M, Dierickx P, Seibert H (2006) Validation of a prediction model for estimating serum concentrations of chemicals which are equivalent to toxic concentrations in vitro. Toxicol In Vitro 20(7):1114–1124. https://doi.org/10.1016/j.tiv.2006.02.002 · DOI
  34. Wetmore BA, Wambaugh JF, Allen B, Ferguson SS, Sochaski MA, Setzer RW, Houck KA, Strope CL, Cantwell K, Judson RS, LeCluyse E, Clewell HJ 3rd, Thomas RS, Andersen ME (2015) Incorporating high-throughput exposure predictions with dosimetry-adjusted in vitro bioactivity to inform chemical toxicity testing. Toxicol Sci. https://doi.org/10.1093/toxsci/kfv171 · DOI · Paper page
  35. Pearce RG, Setzer RW, Strope CL, Sipes NS, Wambaugh JF (2017) httk: R package for high-throughput toxicokinetics. J Stat Softw. https://doi.org/10.18637/jss.v079.i04 · DOI · Paper page
  36. Ingle BL, Veber BC, Nichols JW, Tornero-Velez R (2016) Informing the human plasma protein binding of environmental chemicals by machine learning in the pharmaceutical space: applicability domain and limits of predictability. J Chem Inf Model 56(11):2243–2252. https://doi.org/10.1021/acs.jcim.6b00291 · DOI
  37. Kirman CR, Aylward LL, Wetmore BA, Thomas RS, Sochaski M, Ferguson SS, Csiszar SA, Jolliet O (2015) Quantitative property–property relationship for screening-level prediction of intrinsic clearance: a tool for exposure modeling for high-throughput toxicity screening data. Appl In Vitro Toxicol 1(2):140–146. https://doi.org/10.1089/aivt.2014.0008 · doi:10.1089/aivt.2014.0008
  38. Isaacs KK, Phillips KA, Biryol D, Dionisio KL, Price PS Consumer product chemical weight fractions from ingredient lists. J Expo Sci Environ Epidemiol (in press)
  39. Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Zhou Z, Han L, Karapetyan K, Dracheva S, Shoemaker BA, Bolton E, Gindulyte A, Bryant SH (2011) PubChem’s BioAssay Database. Nucleic Acids Res 40(D1):D400–D412. https://doi.org/10.1093/nar/gkr1132 · DOI · Paper page
  40. PubChem widget documentation. https://pubchem.ncbi.nlm.nih.gov/widget/docs/widget_help.html . Accessed 24 Sept 2017
  41. CompTox Chemistry Dashboard: Google Scholar results set for Atrazine https://scholar.google.com/scholar?hl=en&q=%22NOAEL%22%20AND%20%22Hazard%22%20AND%20%221912-24-9%22%20OR%20%22Atrazine%22 . Accessed 21 Sept 2017
  42. CompTox Chemistry Dashboard: Polychlorinated biphenyls search query against Google Scholar. https://scholar.google.com/scholar?hl=en&q=%22Hazard%22%20AND%20%221336-36-3%22%20OR%20%22Polychlorinated%20biphenyls%22 . Accessed 23 Sept 2017
  43. PubMed web services. https://www.ncbi.nlm.nih.gov/pmc/tools/developers/ . Accessed 25 Sept 2017
  44. Springer Materials: Atrazine http://materials.springer.com/search?searchTerm=MXWJVTOOROXGIU-UHFFFAOYSA-N . Accessed 25 Sept 2017
  45. Rager JE, Strynar MJ, Liang S, McMahen RL, Richard AM, Grulke CM, Wambaugh JF, Isaacs KK, Judson R, Williams AJ, Sobus JR (2016) Linking high resolution mass spectrometry data with exposure and toxicity forecasts to advance high-throughput environmental monitoring. Environ Int 88:269–280. https://doi.org/10.1016/j.envint.2015.12.008 · DOI · Paper page
  46. Newton SR, McMahen RL, Sobus JR, Mansouri K, Williams AJ, McEachran A, Strynar MJ Suspect screening analysis of drinking water using point-of-use filters. Environ Pollut. https://doi.org/10.1016/j.enpol.2017.11.033 · DOI
  47. PubChem: DSSTox substance registration list page https://pubchem.ncbi.nlm.nih.gov/source/EPA%20DSSTox . Accessed 25 Sept 2017
  48. Schymanski EL, Singer HP, Longrée P, Loos M, Ruff M, Stravs MA, Ripollés Vidal C, Hollender J (2014) Strategies to characterize polar organic contamination in wastewater: exploring the capability of high resolution mass spectrometry. Environ Sci Technol 48(3):1811–1818. https://doi.org/10.1021/es4044374 · DOI · Paper page
  49. Schymanski EL, Singer HP, Slobodnik J, Ipolyi IM, Oswald P, Krauss M, Schulze T, Haglund P, Letzel T, Grosse S, Thomaidis NS, Bletsou A, Zwiener C, Ibáñez M, Portolés T, de Boer R, Reid MJ, Onghena M, Kunkel U, Schulz W, Guillon A, Noyon N, Leroy G, Bados P, Bogialli S, Stipaničev D, Rostkowski P, Hollender J (2015) Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis. Anal Bioanal Chem 407(21):6237–6255. https://doi.org/10.1007/s00216-015-8681-7 · DOI · Paper page
  50. Blaženović I, Kind T, Torbašinović H, Obrenović S, Mehta SS, Tsugawa H, Wermuth T, Schauer N, Jahn M, Biedendieck R, Jahn D, Fiehn O (2017) Comprehensive comparison of in silico MS/MS fragmentation tools of the CASMI contest: database boosting is needed to achieve 93% accuracy. J Cheminform. https://doi.org/10.1186/s13321-017-0219-x · DOI
  51. McEachran AD, Sobus JR, Williams AJ (2016) Identifying known unknowns using the US EPA’s CompTox Chemistry Dashboard. Anal Bioanal Chem 409(7):1729–1735. https://doi.org/10.1007/s00216-016-0139-z · DOI
  52. Ruttkies C, Schymanski EL, Wolf S, Hollender J, Neumann S (2016) MetFrag relaunched: incorporating strategies beyond in silico fragmentation. J Cheminform. https://doi.org/10.1186/s13321-016-0115-9 · DOI · Paper page
  53. Schymanski EL, Williams AJ (2017) Open science for identifying “Known Unknown” chemicals. Environ Sci Technol 51(10):5357–5359. https://doi.org/10.1021/acs.est.7b01908 · DOI
  54. Shah I, Liu J, Judson RS, Thomas RS, Patlewicz G (2016) Systematically evaluating read-across prediction and performance using a local validity approach characterized by chemical structure and bioactivity information. Regul Toxicol Pharmacol 79:12–24. https://doi.org/10.1016/j.yrtph.2016.05.008 · DOI

Cited by

See all 1,143

Metadata

Authors
Williams, A. J., Grulke, C. M., Edwards, J., McEachran, A. D., Mansouri, K., Baker, N. C., Patlewicz, G., Shah, I., Wambaugh, J. F., Judson, R. S., & Richard, A. M.
Venue
Journal of Cheminformatics
Published
2017-11-28
Volume
9
Issue
1
Pages
61-61
ISSN
1758-2946 (ISSN-L)
OpenAlex
W2769853272
Cited by
1,143
References
2
FWCI
27.73
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. https://app.cochat.ai/papers/10.1186/s13321-017-0247-6
The paper
Williams, A. J., Grulke, C. M., Edwards, J., McEachran, A. D., Mansouri, K., Baker, N. C., Patlewicz, G., Shah, I., Wambaugh, J. F., Judson, R. S., & Richard, A. M. (2017). The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. Journal of Cheminformatics. https://doi.org/10.1186/s13321-017-0247-6

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.