Application of SVM to predict membrane protein types

J Theor Biol. 2004 Feb 21;226(4):373-6. doi: 10.1016/j.jtbi.2003.08.015.

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.

MeSH terms

  • Algorithms*
  • Amino Acids / analysis
  • Membrane Proteins / chemistry*
  • Membrane Proteins / classification

Substances

  • Amino Acids
  • Membrane Proteins