Transmembrane helix prediction using amino acid property features and latent semantic analysis

Ganapathiraju, Madhavi and Balakrishnan, N and Reddy, Raj and Klein-Seetharaman, Judith (2008) Transmembrane helix prediction using amino acid property features and latent semantic analysis. In: BMC Bioinformatics, 9 (Suppl.). pp. 1-16.

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Abstract

Prediction of transmembrane (TM) helices by statistical methods suffers from lack of sufficient training data. Current best methods use hundreds or even thousands of free parameters in their models which are tuned to fit the little data available for training. Further, they are often restricted to the generally accepted topology "cytoplasmic-transmembrane-extracellular" and cannot adapt to membrane proteins that do not conform to this topology. Recent crystal structures of channel proteins have revealed novel architectures showing that the above topology may not be as universal as previously believed. Thus, there is a need for methods that can better predict TM helices even in novel topologies and families.

Item Type:	Journal Article
Publication:	BMC Bioinformatics
Publisher:	Biomed Central Ltd.
Additional Information:	Copyright of this article belongs to Biomed Central Ltd.
Department/Centre:	Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited:	15 May 2009 07:12
Last Modified:	19 Sep 2010 04:50
URI:	http://eprints.iisc.ac.in/id/eprint/15990

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