An ensemble approach for in silico prediction of Ames mutagenicity

DOI10.1007/s10910-018-0855-zzbMath1401.92075OpenAlexW2791590413WikidataQ57692759 ScholiaQ57692759MaRDI QIDQ1617490

Miguel Ángel Gómez-Nieto, Nicolás García-Pedrajas, Gonzalo Cerruela García, Irene Luque Ruiz

Publication date: 8 November 2018

Published in: Journal of Mathematical Chemistry (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10910-018-0855-z

zbMATH Keywords

QSARensembles of classifiersmutagenicity prediction

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40)

Related Items

Prediction of the datasets modelability for the building of QSAR classification models by means of the centroid based rivality index

Uses Software

• Rdkit

Cites Work

• Bagging predictors
• Boosting random subspace method
• Nonparametric Discriminant Analysis
• Random forests
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