ArticleChemical research in toxicology2022
Automating Predictive Toxicology Using ComptoxAI.
Article in Chemical research in toxicology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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
15 citing papers in PubMed.
- Semantic knowledge improves molecular machine learning for chemical toxicity prediction.iScience · 2026Article
- Context-Aware Multilevel Classification of Semantic Relations in Drug-Adverse Drug Reaction (ADR) Networks-Predicting Drug-Induced Liver Injury (DILI) as a Case Study.Chemical research in toxicology · 2026Article
- Eras of bioinformatics technologies from command-line interfaces to artificial intelligence (AI) chatbots.Briefings in bioinformatics · 2026Review
- Advances in Cytotoxicity Testing: From In Vitro Assays to In Silico Models.International journal of molecular sciences · 2025Review
- Artificial Intelligence (AI) in Pharmaceutical Formulation and Dosage Calculations.Pharmaceutics · 2025Review
- Graph Neural Network-Based Toxicity Prediction by Integrating Molecular Fingerprints and Knowledge Graph Features.Toxics · 2025Article
- The FAIR AOP roadmap for 2025: Advancing findability, accessibility, interoperability, and re-usability of adverse outcome pathways.Computational toxicology (Amsterdam, Netherlands) · 2025Article
- The 3C (Cell Culture, Computer Simulation, Clinical Trial) Solution for Optimizing the 3R (Replace, Reduction, Refine) Framework during Preclinical Research Involving Laboratory Animals.ACS pharmacology & translational science · 2025Review
- The TOXIN knowledge graph: supporting animal-free risk assessment of cosmetics.Database : the journal of biological databases and curation · 2025Article
- The computationally guided design of selective targeters of multiple proteins (STaMPs) as a new opportunity for small molecule drug discovery.Frontiers in pharmacology · 2025Review
- The Alzheimer's Knowledge Base: A Knowledge Graph for Alzheimer Disease Research.Journal of medical Internet research · 2024Article
- Cost-effectiveness analysis of insecticide ban aimed at preventing Parkinson's disease in Central California.The Science of the total environment · 2024Article
- ExEmPLAR (Extracting, Exploring, and Embedding Pathways Leading to Actionable Research): a user-friendly interface for knowledge graph mining.Bioinformatics (Oxford, England) · 2024Article
- Knowledge graph aids comprehensive explanation of drug and chemical toxicity.CPT: pharmacometrics & systems pharmacology · 2023Article
- Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science.Computational toxicology (Amsterdam, Netherlands) · 2023Article
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.
Funding
Abstract
ComptoxAI is a new data infrastructure for computational and artificial intelligence research in predictive toxicology. Here, we describe and showcase ComptoxAI's graph-structured knowledge base in the context of three real-world use-cases, demonstrating that it can rapidly answer complex questions about toxicology that are infeasible using previous technologies and data resources. These use-cases each demonstrate a tool for information retrieval from the knowledge base being used to solve a specific task: The "shortest path" module is used to identify mechanistic links between perfluorooctanoic acid (PFOA) exposure and nonalcoholic fatty liver disease; the "expand network" module identifies communities that are linked to dioxin toxicity; and the quantitative structure-activity relationship (QSAR) dataset generator predicts pregnane X receptor agonism in a set of 4,021 pesticide ingredients. The contents of ComptoxAI's source data are rigorously aggregated from a diverse array of public third-party databases, and ComptoxAI is designed as a free, public, and open-source toolkit to enable diverse classes of users including biomedical researchers, public health and regulatory officials, and the general public to predict toxicology of unknowns and modes of action.
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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.