Literature DB >> 14759643

Application of SVM to predict membrane protein types.

Yu-Dong Cai1, Pong-Wong Ricardo, Chih-Hung Jen, Kuo-Chen Chou.   

Abstract

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.

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Year:  2004        PMID: 14759643     DOI: 10.1016/j.jtbi.2003.08.015

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  19 in total

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