AUTHOR=Maunz Andreas , Gütlein Martin , Rautenberg Micha , Vorgrimmler David , Gebele Denis , Helma Christoph TITLE=lazar: a modular predictive toxicology framework JOURNAL=Frontiers in Pharmacology VOLUME=4 YEAR=2013 URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2013.00038 DOI=10.3389/fphar.2013.00038 ISSN=1663-9812 ABSTRACT=

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.