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Prediction of Membrane Proteins in Mycobacterium tuberculosis Using a Support Vector Machine Algorithm

To cite this article:
Joanne I. Yeh and Lisong Mao and. Journal of Computational Biology. January/February 2006, 13(1): 126-129. doi:10.1089/cmb.2006.13.126.

Published in Volume: 13 Issue 1: February 10, 2006

Author information

Joanne I. Yeh
Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI 20906.
Department of Chemistry, Brown University, Providence, RI 20906.
Current address: University of Pittsburgh Medical School, Department of Structural Biology, 3501 5th Avenue, Pittsburgh, PA 15260.
Lisong Mao
Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, RI 20906.

ABSTRACT

We report our finding of linear clustering of signal sequences at the N-terminus of M.tb membrane proteins, directing membrane localization. Although it is widely accepted that membrane proteins have signal peptides at the N-terminus, statistical ensemble analysis of Support Vector Machine prediction results indicate that M.tb membrane proteins have embedded N-terminal sequence patterns beyond the signal peptides previously identified in E. coli. The additional patterns at the N-terminus of M.tb membrane proteins may have correlations to their unique enzymatic functions and unusual characteristics such as membrane interaction in pathogenes

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