lazar: a modular predictive toxicology framework

نویسندگان

  • Andreas Maunz
  • Martin Gütlein
  • Micha Rautenberg
  • David Vorgrimmler
  • Denis Gebele
  • Christoph Helma
چکیده

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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عنوان ژورنال:

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2013