A statistical physics perspective on alignment-independent protein sequence comparison.

Amit K. Chattopadhyay, Diar Nasiev, Darren R. Flower*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Motivation: Within bioinformatics, the textual alignment of amino acid sequences has long dominated the determination of similarity between proteins, with all that implies for shared structure, function, and evolutionary descent. Despite the relative success of modern-day sequence alignment algorithms, so-called alignment-free approaches offer a complementary means of determining and expressing similarity, with potential benefits in certain key applications, such as regression analysis of protein structure-function studies, where alignment-base similarity has performed poorly.

Results: Here, we offer a fresh, statistical physics-based perspective focusing on the question of alignment-free comparison, in the process adapting results from “first passage probability distribution” to summarize statistics of ensemble averaged amino acid propensity values. In this paper, we introduce and elaborate this approach.
Original languageEnglish
Pages (from-to)2469-2474
Number of pages6
JournalBioinformatics
Volume31
Issue number15
Early online date25 Mar 2015
DOIs
Publication statusPublished - 1 Aug 2015

Bibliographical note

© The Author(s) 2015. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Funding: Work supported by Aston University.

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