Protein & Peptide Letters

Prof. Ben M. Dunn  
Department of Biochemistry and Molecular Biology
University of Florida
College of Medicine
P.O. Box 100245
Gainesville, FL
USA
Email: bdunn@ufl.edu

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

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

Affiliation: Laboratory of Theoretical Biophysics, Department of Physics, College of Sciences and Technology,Inner Mongolia University, Hohhot 010021, China.

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

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Article Details

VOLUME: 15
ISSUE: 6
Page: [612 - 616]
Pages: 5
DOI: 10.2174/092986608784966930
Price: $58