4.4 Article

Application of SVM to predict membrane protein types

Journal

JOURNAL OF THEORETICAL BIOLOGY
Volume 226, Issue 4, Pages 373-376

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jtbi.2003.08.015

Keywords

type I membrane protein; type II membrane protein; multipass transmembrane proteins; lipid chain-anchored membrane proteins; GPI-anchored membrane proteins; chou's invariance theorem

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As a continuous effort to develop automated methods for predicting membrane protein types that was initiated by Chou and Elrod (PROTEINS: Structure, Function, and Genetics, 1999, 34, 137-153), the support vector machine (SVM) is introduced. Results obtained through re-substitution, jackknife, and independent data set tests, respectively, have indicated that the SVM approach is quite a promising one, suggesting that the covariant discriminant algorithm (Chou and Elrod, Protein Eng. 12 (1999) 107) and SVM if effectively complemented with each other, will become a powerful tool for predicting membrane protein types and the other protein attributes as well. (C) 2003 Elsevier Ltd. All rights reserved.

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