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BioMed Research International
Volume 2014, Article ID 935719, 8 pages
http://dx.doi.org/10.1155/2014/935719
Research Article

Predicting the Types of J-Proteins Using Clustered Amino Acids

1School of Public Health, Hebei United University, Tangshan 063000, China
2Key Laboratory for Neuroinformation of Ministry of Education, Center of Bioinformatics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
3Department of Physics, School of Sciences, Center for Genomics and Computational Biology, Hebei United University, Tangshan 063000, China
4The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot 010021, China

Received 24 January 2014; Revised 4 March 2014; Accepted 13 March 2014; Published 2 April 2014

Academic Editor: Dong Wang

Copyright © 2014 Pengmian Feng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

J-proteins are molecular chaperones and present in a wide variety of organisms from prokaryote to eukaryote. Based on their domain organizations, J-proteins can be classified into 4 types, that is, Type I, Type II, Type III, and Type IV. Different types of J-proteins play distinct roles in influencing cancer properties and cell death. Thus, reliably annotating the types of J-proteins is essential to better understand their molecular functions. In the present work, a support vector machine based method was developed to identify the types of J-proteins using the tripeptide composition of reduced amino acid alphabet. In the jackknife cross-validation, the maximum overall accuracy of 94% was achieved on a stringent benchmark dataset. We also analyzed the amino acid compositions by using analysis of variance and found the distinct distributions of amino acids in each family of the J-proteins. To enhance the value of the practical applications of the proposed model, an online web server was developed and can be freely accessed.