Quasi-consensus-based comparison of profile hidden Markov models for protein sequences

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Abstract

A simple approach for the sensitive detection of distant relationships among protein families and for sequence-structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile-profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod © The Author 2005. Published by Oxford University Press. All rights reserved.

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Kahsay, R. Y., Wang, G., Gao, G., Liao, L., & Dunbrack, R. (2005). Quasi-consensus-based comparison of profile hidden Markov models for protein sequences. Bioinformatics, 21(10), 2287–2293. https://doi.org/10.1093/bioinformatics/bti374

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