Protein & Peptide Letters

Author(s): Feng-Min Li and Qian-Zhong Li

DOI: 10.2174/092986608784966930

Predicting Protein Subcellular Location Using Chous Pseudo Amino Acid Composition and Improved Hybrid Approach

Page: [612 - 616] Pages: 5

  • * (Excluding Mailing and Handling)

Abstract

The location of a protein in a cell is closely correlated with its biological function. Based on the concept that the protein subcellular location is mainly determined by its amino acid and pseudo amino acid composition (PseAA), a new algorithm of increment of diversity combined with support vector machine is proposed to predict the protein subcellular location. The subcellular locations of plant and non-plant proteins are investigated by our method. The overall prediction accuracies in jackknife test are 88.3% for the eukaryotic plant proteins and 92.4% for the eukaryotic non-plant proteins, respectively. In order to estimate the effect of the sequence identity on predictive result, the proteins with sequence identity 40% are selected. The overall success rates of prediction are 86.2% and 92.3% for plant and non-plant proteins in jackknife test, respectively.

Keywords: Subcellular location, increment of diversity, support vector machine, Chou's pseudo amino acid composition