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MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions

Title:

MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions

Al-Shatnawi, Mufleh Saleh, Ahmad, M. Omair and S. Swamy, M. N. (2015) MSAIndelFR: a scheme for multiple protein sequence alignment using information on indel flanking regions. BMC Bioinformatics, 16 (1). p. 393. ISSN 1471-2105

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Official URL: http://dx.doi.org/10.1186/s12859-015-0826-3

Abstract

Background
The alignment of multiple protein sequences is one of the most commonly performed tasks in bioinformatics. In spite of considerable research and efforts that have been recently deployed for improving the performance of multiple sequence alignment (MSA) algorithms, finding a highly accurate alignment between multiple protein sequences is still a challenging problem.

Results
We propose a novel and efficient algorithm called, MSAIndelFR, for multiple sequence alignment using the information on the predicted locations of IndelFRs and the computed average log–loss values obtained from IndelFR predictors, each of which is designed for a different protein fold. We demonstrate that the introduction of a new variable gap penalty function based on the predicted locations of the IndelFRs and the computed average log–loss values into the proposed algorithm substantially improves the protein alignment accuracy. This is illustrated by evaluating the performance of the algorithm in aligning sequences belonging to the protein folds for which the IndelFR predictors already exist and by using the reference alignments of the four popular benchmarks, BAliBASE 3.0, OXBENCH, PREFAB 4.0, and SABRE (SABmark 1.65).

Conclusions
We have proposed a novel and efficient algorithm, the MSAIndelFR algorithm, for multiple protein sequence alignment incorporating a new variable gap penalty function. It is shown that the performance of the proposed algorithm is superior to that of the most–widely used alignment algorithms, Clustal W2, Clustal Omega, Kalign2, MSAProbs, MAFFT, MUSCLE, ProbCons and Probalign, in terms of both the sum–of–pairs and total column metrics.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Refereed:Yes
Authors:Al-Shatnawi, Mufleh Saleh and Ahmad, M. Omair and S. Swamy, M. N.
Journal or Publication:BMC Bioinformatics
Date:2015
Funders:
  • Concordia Open Access Author Fund
Digital Object Identifier (DOI):10.1186/s12859-015-0826-3
Keywords:Multiple sequence alignment, Indel flanking regions, PPM IndelFR predictor, Dynamic programming
ID Code:982257
Deposited By: Danielle Dennie
Deposited On:21 Mar 2017 14:25
Last Modified:18 Jan 2018 17:54
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