ArticleComputational toxicology (Amsterdam, Netherlands)2019
EPA's DSSTox database: History of development of a curated chemistry resource supporting computational toxicology research.
Article in Computational toxicology (Amsterdam, Netherlands), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
103 citing papers in PubMed, 2 syntheses or guidelines pooled it, 183 citations in OpenAlex.
- Application of systematic evidence mapping to identify available data on the potential human health hazards of selected market-relevant azo dyes.Environment international · 2023Pooled it
- Weight of evidence for cross-species conservation of androgen receptor-based biological activity.Toxicological sciences : an official journal of the Society of Toxicology · 2023Pooled it
- Semantic knowledge improves molecular machine learning for chemical toxicity prediction.iScience · 2026Article
- AI/ML-based computational models for toxicity prediction.Environmental science and pollution research international · 2026Review
- Structure-informed deep generation enables de novo metabolite annotation in untargeted metabolomics.Nature communications · 2026Article
- Integration of Machine Learning With PBPK and QSAR Modeling Approaches to Facilitate Drug Discovery and Development.CPT: pharmacometrics & systems pharmacology · 2026Review
- Silicone-Foam Passive Air Samplers for Combined Target and Nontarget Chemical Profiling and Toxicity Assessment of Airborne Exposomes.Environmental science & technology · 2026Article
- Large-scale generation of in silico based spectral libraries to annotate dark chemical space features in non-target analysis.Analytical and bioanalytical chemistry · 2025Article
- Identifying Gene Predictors of Chemicals Linked With Breast Cancer: A Machine Learning Analysis of MCF7 Cellular Transcriptomic Screening Data.Environmental and molecular mutagenesis · 2025Article
- Building a compendium of expert driven read-across cases to facilitate an analysis of the contribution that different similarity contexts play in read-across performance.Computational toxicology (Amsterdam, Netherlands) · 2025Article
- The FAIR AOP roadmap for 2025: Advancing findability, accessibility, interoperability, and re-usability of adverse outcome pathways.Computational toxicology (Amsterdam, Netherlands) · 2025Article
- Development of the toxicity values database, ToxValDB: A curated resource for experimental and derived human health-relevant toxicity data.Computational toxicology (Amsterdam, Netherlands) · 2025Article
- Unveiling the Endocrine-Disrupting Potential of Plant-Derived Compounds: An Ecotoxicological Review.Toxins · 2025Review
- How to crack a SMILES: automatic crosschecked chemical structure resolution across multiple services using MoleculeResolver.Journal of cheminformatics · 2025Article
- Artificial Intelligence-Driven Drug Toxicity Prediction: Advances, Challenges, and Future Directions.Toxics · 2025Review
- ExpoPath: A method for identifying and annotating exposure pathways from chemical co-occurrence networks.The Science of the total environment · 2025Article
- Can graph similarity metrics be helpful for analogue identification as part of a read-across approach?Computational toxicology (Amsterdam, Netherlands) · 2025Article
- Multilaboratory Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry for the Screening of 1087 Pesticides in Fresh Fruits and Vegetables.Journal of agricultural and food chemistry · 2025Article
- Automated QA/QC reporting for non-targeted analysis: a demonstration of "INTERPRET NTA" with de facto water reuse data.Analytical and bioanalytical chemistry · 2025Article
- Applicability of In Silico New Approach Methods for the Risk Assessment of Tattoo Ink Ingredients.Environmental and molecular mutagenesis · 2025Article
43 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The US Environmental Protection Agency's (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database, launched publicly in 2004, currently exceeds 875 K substances spanning hundreds of lists of interest to EPA and environmental researchers. From its inception, DSSTox has focused curation efforts on resolving chemical identifier errors and conflicts in the public domain towards the goal of assigning accurate chemical structures to data and lists of importance to the environmental research and regulatory community. Accurate structure-data associations, in turn, are necessary inputs to structure-based predictive models supporting hazard and risk assessments. In 2014, the legacy, manually curated DSSTox_V1 content was migrated to a MySQL data model, with modern cheminformatics tools supporting both manual and automated curation processes to increase efficiencies. This was followed by sequential auto-loads of filtered portions of three public datasets: EPA's Substance Registry Services (SRS), the National Library of Medicine's ChemID, and PubChem. This process was constrained by a key requirement of uniquely mapped identifiers (i.e., CAS RN, name and structure) for each substance, rejecting content where any two identifiers were conflicted either within or across datasets. This rejected content highlighted the degree of conflicting, inaccurate substance-structure ID mappings in the public domain, ranging from 12% (within EPA SRS) to 49% (across ChemID and PubChem). Substances successfully added to DSSTox from each auto-load were assigned to one of five
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.