Publication | Open Access
lazar: a modular predictive toxicology framework
169
Citations
25
References
2013
Year
EngineeringHit IdentificationMedical ToxicologyPathologyMedicinal ChemistryData ScienceToxicologyLazy Structure-activity RelationshipsLazar FrameworkClinical ToxicologyPredictive ToxicologyModular FrameworkPharmacologyTarget PredictionForensic ToxicologyComputational BiologyRational Drug DesignEnvironmental ToxicologyMedicineQuantitative Structure-activity RelationshipDrug DiscoveryToxicogenomicsDrug Analysis
lazar (lazy structure-activity relationships) is a modular framework for predictive toxicology. Similar to the read across procedure in toxicological risk assessment, lazar creates local QSAR (quantitative structure-activity relationship) models for each compound to be predicted. Model developers can choose between a large variety of algorithms for descriptor calculation and selection, chemical similarity indices, and model building. This paper presents a high level description of the lazar framework and discusses the performance of example classification and regression models.
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