Article
Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms.
Journal of chemical information and computer sciences - 1 Jan 2000
Sorich Michael J, Miners John O, McKinnon Ross A, Winkler David A, Burden Frank R, Smith Paul A
Abstract excerpt
Partial least squares discriminant analysis (PLSDA), Bayesian regularized artificial neural network (BRANN), and support vector machine (SVM) methodologies were compared by their ability to classify substrates and nonsubstrates of 12 isoforms of human UDP-glucuronosyltransferase (UGT), an enzyme "superfamily" involved in the metabolism of drugs, nondrug xenobiotics, and endogenous compounds. Simple...
Read the complete abstract on PubMedTopics
Share this publication in a Topic to start or enrich a Post.