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.