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J. Biol. Chem., Vol. 281, Issue 9, 5357-5363, March 3, 2006

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Prediction of Mitochondrial Proteins Using Support Vector Machine and Hidden Markov Model^*

From the Institute of Microbial Technology, Sector 39-A, Chandigarh 160036, India

Mitochondria are considered as one of the core organelles of eukaryotic cells hence prediction of mitochondrial proteins is one of the major challenges in the field of genome annotation. This study describes a method, MitPred, developed for predicting mitochondrial proteins with high accuracy. The data set used in this study was obtained from Guda, C., Fahy, E. & Subramaniam, S. (2004) Bioinformatics 20, 1785–1794. First support vector machine-based modules/methods were developed using amino acid and dipeptide composition of proteins and achieved accuracy of 78.37 and 79.38%, respectively. The accuracy of prediction further improved to 83.74% when split amino acid composition (25 N-terminal, 25 C-terminal, and remaining residues) of proteins was used. Then BLAST search and support vector machine-based method were combined to get 88.22% accuracy. Finally we developed a hybrid approach that combined hidden Markov model profiles of domains (exclusively found in mitochondrial proteins) and the support vector machine-based method. We were able to predict mitochondrial protein with 100% specificity at a 56.36% sensitivity rate and with 80.50% specificity at 98.95% sensitivity. The method estimated 9.01, 6.35, 4.84, 3.95, and 4.25% of proteins as mitochondrial in Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, mouse, and human proteomes, respectively. MitPred was developed on the above hybrid approach.

Received for publication, October 11, 2005 , and in revised form, December 7, 2005.

^* This work was supported by the Council of Scientific and Industrial Research and the Department of Biotechnology, Government of India. This report has Institute of Microbial Technology communication number 052/2005. The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

The on-line version of this article (available at http://www.jbc.org) contains supplemental Figs. S1 and S2.

¹ To whom correspondence should be addressed: Bioinformatics Centre, Inst. of Microbial Technology, Sector 39-A, Chandigarh 160036, India. Tel.: 91-172-2690557 or -2690225; Fax: 91-172-2690632 or -2690585; E-mail: raghava{at}imtech.res.in.

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