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Applicability domain of QSAR models
- Source :
- Diss., 2011, 149 S.
- Publication Year :
- 2011
-
Abstract
- In recent decades, computational models have gained popularity for predictions of biological activities and physico-chemical properties. The major limiting point of computational models is a lack for a clear definition of their applicability domain. The work introduces the methodology for the AD assessment and performs a comprehensive benchmarking analysis of existing and new approaches. The practical AD assessment is demonstrated in a number of studies on the prediction of such properties as mutagenicity (Ames test), toxicity (inhibition growth concentration), lipophilicity and cytochromes inhibition. It is shown that the AD approaches allow to estimate the prediction accuracy for every compound individually and, thereby, to identify highly accurate predictions with the accuracy close to that of experimental measurements. All the introduced AD methods are implemented as a part of a new platform for chemical modeling (OCHEM) and are publicly available online at http://ochem.eu.
- Subjects :
- QSAR
chemoinformatics
applicability domain
machine learning
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Diss., 2011, 149 S.
- Accession number :
- edsair.od......3474..22012bd76a3defc9f520ffacc68cede3