ArticleALTEX2017
Computational approaches to chemical hazard assessment.
Article in ALTEX, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 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
22 citing papers in PubMed.
- Systematic validation of graph neural network explanations against adverse outcome pathway reactive centers for skin sensitization.Journal of cheminformatics · 2026Article
- Optimizing skin sensitization prediction across activity cliffs: a comparative analysis of K-nearest neighbours vs random Forest.Frontiers in toxicology · 2026Article
- Navigating the AI Frontier in Toxicology: Trends, Trust, and Transformation.Current environmental health reports · 2025Review
- HazChemNet: A Deep Learning Model for Hazardous Chemical Prediction.International journal of molecular sciences · 2025Article
- Quantitative structure-activity relationships of chemical bioactivity toward proteins associated with molecular initiating events of organ-specific toxicity.Journal of cheminformatics · 2024Article
- Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).Archives of toxicology · 2024Review
- Assessment of the Effects of Chitosan, Chitooligosaccharides and Their Derivatives onMolecules (Basel, Switzerland) · 2022Article
- Multi-Strategy Assessment of Different Uses of QSAR under REACH Analysis of Alternatives to Advance Information Transparency.International journal of environmental research and public health · 2022Article
- Mitochondria as the Target of Hepatotoxicity and Drug-Induced Liver Injury: Molecular Mechanisms and Detection Methods.International journal of molecular sciences · 2022Review
- Editorial: Application of computational tools to health and environmental sciences, Volume II.Frontiers in pharmacology · 2022Article
- In Vitro Liver Toxicity Testing of Chemicals: A Pragmatic Approach.International journal of molecular sciences · 2021Review
- Mapping Chemical Respiratory Sensitization: How Useful Are Our Current Computational Tools?Chemical research in toxicology · 2021Article
- Evaluation of the global performance of eight in silico skin sensitization models using human data.ALTEX · 2021Article
- Are we rushing too much?Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association · 2020Article
- Article
- In silico prediction of toxicity and its applications for chemicals at work.Toxicology and environmental health sciences · 2020Review
- Internationalization of read-across as a validated new approach method (NAM) for regulatory toxicology.ALTEX · 2020Article
- Predicting toxicity of chemicals: software beats animal testing.EFSA journal. European Food Safety Authority · 2019Article
- Computational Assessment of the Pharmacological Profiles of Degradation Products of Chitosan.Frontiers in bioengineering and biotechnology · 2019Article
- Big-data and machine learning to revamp computational toxicology and its use in risk assessment.Toxicology research · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Computational prediction of toxicity has reached new heights as a result of decades of growth in the magnitude and diversity of biological data. Public packages for statistics and machine learning make model creation faster. New theory in machine learning and cheminformatics enables integration of chemical structure, toxicogenomics, simulated and physical data in the prediction of chemical health hazards, and other toxicological information. Our earlier publications have characterized a toxicological dataset of unprecedented scale resulting from the European REACH legislation (Registration Evaluation Authorisation and Restriction of Chemicals). These publications dove into potential use cases for regulatory data and some models for exploiting this data. This article analyzes the options for the identification and categorization of chemicals, moves on to the derivation of descriptive features for chemicals, discusses different kinds of targets modeled in computational toxicology, and ends with a high-level perspective of the algorithms used to create computational toxicology models.
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.