ArticleMolecular diversity2006
Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity.
Article in Molecular diversity, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 109 citations in OpenAlex.
- LMF-CP: An Interpretable Multimodal Late-Fusion Framework for Compound Carcinogenicity Prediction.International journal of molecular sciences · 2026Article
- Artificial Intelligence and Machine Learning-Based Approaches for Genetic Damage Prediction.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Mutagenicity and carcinogenicity prediction of sugar substitutes: anToxicology research · 2025Article
- Evaluating different web applications to assess the toxicity of plasticizers.Scientific reports · 2022Article
- Review
- Computational Approaches in Preclinical Studies on Drug Discovery and Development.Frontiers in chemistry · 2020Review
- Novel Thiazolidin-4-ones as Potential Non-nucleoside Inhibitors of HIV-1 Reverse Transcriptase.Molecules (Basel, Switzerland) · 2019Article
- Biological Safety Studies and Simultaneous Determination of Linagliptin and Synthetic Impurities by LC-PDA.Journal of analytical methods in chemistry · 2019Article
- Predicting Aromatic Amine Mutagenicity with Confidence: A Case Study Using Conformal Prediction.Biomolecules · 2018Article
- CarcinoPred-EL: Novel models for predicting the carcinogenicity of chemicals using molecular fingerprints and ensemble learning methods.Scientific reports · 2017Article
- Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability.Journal of cheminformatics · 2016Article
- lazar: a modular predictive toxicology framework.Frontiers in pharmacology · 2013Article
- Adaptation of high-throughput screening in drug discovery-toxicological screening tests.International journal of molecular sciences · 2012Review
- Open Babel: An open chemical toolbox.Journal of cheminformatics · 2011Article
- Alternatives to animal testing: current status and future perspectives.Archives of toxicology · 2011Article
- Towards interoperable and reproducible QSAR analyses: Exchange of datasets.Journal of cheminformatics · 2010Article
- Accurate and interpretable computational modeling of chemical mutagenicity.Journal of chemical information and modeling · 2008Article
- A novel automated lazy learning QSAR (ALL-QSAR) approach: method development, applications, and virtual screening of chemical databases using validated ALL-QSAR models.Journal of chemical information and modelingArticle
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
lazar is a new tool for the prediction of toxic properties of chemical structures. It derives predictions for query structures from a database with experimentally determined toxicity data. lazar generates predictions by searching the database for compounds that are similar with respect to a given toxic activity and calculating the prediction from their activities. Apart form the prediction, lazar provides the rationales (structural features and similar compounds) for the prediction and a reliable condence index that indicates, if a query structure falls within the applicability domain of the training database.Leave-one-out (LOO) crossvalidation experiments were carried out for 10 carcinogenicity endpoints ({female/male} {hamster/mouse/rat} carcinogenicity and aggregate endpoints {hamster/mouse/rat} carcinogenicity and rodent carcinogenicity) and Salmonella mutagenicity from the Carcinogenic Potency Database (CPDB). An external validation of Salmonella mutagenicity predictions was performed with a dataset of 3895 structures. Leave-one-out and external validation experiments indicate that Salmonella mutagenicity can be predicted with 85% accuracy for compounds within the applicability domain of the CPDB. The LOO accuracy of lazar predictions of rodent carcinogenicity is 86%, the accuracies for other carcinogenicity endpoints vary between 78 and 95% for structures within the applicability domain.
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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.