ReviewCritical reviews in toxicology2024
Molecular similarity in chemical informatics and predictive toxicity modeling: from quantitative read-across (q-RA) to quantitative read-across structure-activity relationship (q-RASAR) with the application of machine learning.
Review in Critical reviews in toxicology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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.
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Who cites it
17 citing papers in PubMed.
- A dual-view fusion framework using residual gated graph convolution and Mamba for metabolite-disease association prediction with explorations on salivary metabolites.Journal of computer-aided molecular design · 2026Article
- Machine learning-based prediction of SARS-CoV-2 bioactivity: integrating ICBMC bioinformatics · 2026Article
- Safe-by-redesign guidance for toxic industrial chemicals using explainable artificial intelligence: Introducing the DETOX-QSAR model.Scientific reports · 2026Article
- KidneyTox_v1.0 enables explainable artificial intelligence prediction of nephrotoxicity in small molecules.Scientific reports · 2026Article
- In silico identification of novel PTP1B inhibitors by the investigation of molecular mechanism, QSAR, and DFT studies.In silico pharmacology · 2026Article
- In Silico Approaches in Predictive Genetic Toxicology.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Recent Advances in Machine Learning Models for Predicting Toxicity of Inorganic Nanoparticles.Chem & bio engineering · 2025Review
- 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
- Titania: an integrated tool for in silico molecular property prediction and NAM-based modeling.Molecular diversity · 2025Article
- Can graph similarity metrics be helpful for analogue identification as part of a read-across approach?Computational toxicology (Amsterdam, Netherlands) · 2025Article
- Revisiting the approaches to DNA damage detection in genetic toxicology: insights and regulatory implications.BioData mining · 2025Article
- Machine learning assisted classification RASAR modeling for the nephrotoxicity potential of a curated set of orally active drugs.Scientific reports · 2025Article
- Mechanistic read-across comes of age: a comparative appraisal of EFSA 2025 guidance, ECHA's RAAF, and good read-across practice.Frontiers in toxicology · 2025Review
- Overview of Computational Toxicology Methods Applied in Drug and Green Chemical Discovery.Journal of xenobiotics · 2024Review
- Development of hybrid models by the integration of the read-across hypothesis with the QSAR framework for the assessment of developmental and reproductive toxicity (DART) tested according to OECD TG 414.Toxicology reports · 2024Article
- Article
- The application of chemical similarity measures in an unconventional modeling framework c-RASAR along with dimensionality reduction techniques to a representative hepatotoxicity dataset.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
This article aims to provide a comprehensive critical, yet readable, review of general interest to the chemistry community on molecular similarity as applied to chemical informatics and predictive modeling with a special focus on read-across (RA) and read-across structure-activity relationships (RASAR). Molecular similarity-based computational tools, such as quantitative structure-activity relationships (QSARs) and RA, are routinely used to fill the data gaps for a wide range of properties including toxicity endpoints for regulatory purposes. This review will explore the background of RA starting from how structural information has been used through to how other similarity contexts such as physicochemical, absorption, distribution, metabolism, and elimination (ADME) properties, and biological aspects are being characterized. More recent developments of RA's integration with QSAR have resulted in the emergence of novel models such as ToxRead, generalized read-across (GenRA), and quantitative RASAR (q-RASAR). Conventional QSAR techniques have been excluded from this review except where necessary for context.
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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.