By Topic

BPPS: an algorithm for analyzing protein sequence alignments

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Liu, J. ; Dept. of Stat., Harvard Univ., USA

Aligning multiple biopolymer sequences has been recognized as a central activity in bioinformatics research. But the analysis of the resulting alignments has not been rigorously formulated and mathematically tackled. We have developed statistical procedures to decompose the multiple alignments into distinct categories and to pinpoint critical structural features within each category. A central part of our statistical procedures is a novel algorithm called the Bayesian partitioning with pattern selection (BPPS), which is based on a two-way mixture model and can simultaneously classify protein sequences into distinct subfamilies and select conserved positions that are characteristic of these subfamilies. When applied to P-loop GTPases, this revealed within Rab, Rho, Ras, and Ran a canonical network of molecular interactions centered on bound nucleotide. This network presumably performs a crucial structural and/or mechanistic role considering that it has persisted for more than a billion years after the divergence of these families.

Published in:

Bioinformatics Conference, 2003. CSB 2003. Proceedings of the 2003 IEEE

Date of Conference:

11-14 Aug. 2003