ArticleChemical research in toxicology2023
The Good, The Bad, and The Perplexing: Structural Alerts and Read-Across for Predicting Skin Sensitization Using Human Data.
Article in Chemical research in toxicology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Article
- Optimizing skin sensitization prediction across activity cliffs: a comparative analysis of K-nearest neighbours vs random Forest.Frontiers in toxicology · 2026Article
- Unified and explainable molecular representation learning for imperfectly annotated data from the hypergraph view.Nature communications · 2025Article
- Estimation of the Skin Sensitization Potential of Chemicals of the Acyl Domain Using DFT-Based Calculations.Chemical research in toxicology · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
In our earlier work (Golden et al., 2021), we showed 70-80% accuracies for several skin sensitization computational tools using human data. Here, we expanded the data set using the NICEATM human skin sensitization database to create a final data set of 1355 discrete chemicals (largely negative, ∼70%). Using this expanded data set, we analyzed model performance and evaluated mispredictions using Toxtree (v 3.1.0), OECD QSAR Toolbox (v 4.5), VEGA's (1.2.0 BETA) CAESAR (v 2.1.7), and a
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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.