Literature DB >> 11108703

An iterative method for faster sum-of-pairs multiple sequence alignment.

K Reinert1, J Stoye, T Will.   

Abstract

MOTIVATION: Multiple sequence alignment is an important tool in computational biology. In order to solve the task of computing multiple alignments in affordable time, the most commonly used multiple alignment methods have to use heuristics. Nevertheless, the computation of optimal multiple alignments is important in its own right, and it provides a means of evaluating heuristic approaches or serves as a subprocedure of heuristic alignment methods.
RESULTS: We present an algorithm that uses the divide-and-conquer alignment approach together with recent results on search space reduction to speed up the computation of multiple sequence alignments. The method is adaptive in that depending on the time one wants to spend on the alignment, a better, up to optimal alignment can be obtained. To speed up the computation in the optimal alignment step, we apply the alpha(*) algorithm which leads to a procedure provably more efficient than previous exact algorithms. We also describe our implementation of the algorithm and present results showing the effectiveness and limitations of the procedure.

Mesh:

Substances:

Year:  2000        PMID: 11108703     DOI: 10.1093/bioinformatics/16.9.808

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

1.  MISHIMA--a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data.

Authors:  Kirill Kryukov; Naruya Saitou
Journal:  BMC Bioinformatics       Date:  2010-03-18       Impact factor: 3.169

2.  Meta-alignment with crumble and prune: partitioning very large alignment problems for performance and parallelization.

Authors:  Krishna M Roskin; Benedict Paten; David Haussler
Journal:  BMC Bioinformatics       Date:  2011-05-10       Impact factor: 3.307

3.  A fast parallel algorithm for finding the longest common sequence of multiple biosequences.

Authors:  Yixin Chen; Andrew Wan; Wei Liu
Journal:  BMC Bioinformatics       Date:  2006-12-12       Impact factor: 3.169

4.  DivA: detection of non-homologous and very divergent regions in protein sequence alignments.

Authors:  Marie Lisandra Zepeda Mendoza; Sanne Nygaard; Rute R da Fonseca
Journal:  BMC Res Notes       Date:  2014-11-18

5.  Disease Sequences High-Accuracy Alignment Based on the Precision Medicine.

Authors:  ManZhi Li; HaiXia Long; HongTao Wang; HaiYan Fu; Dong Xu; YouJian Shen; YuHua Yao; Bo Liao
Journal:  Biomed Res Int       Date:  2018-02-22       Impact factor: 3.411

6.  Post-Alignment Adjustment and Its Automation.

Authors:  Xuhua Xia
Journal:  Genes (Basel)       Date:  2021-11-18       Impact factor: 4.096

7.  Identifying foldable regions in protein sequence from the hydrophobic signal.

Authors:  Chi N I Pang; Kuang Lin; Merridee A Wouters; Jaap Heringa; Richard A George
Journal:  Nucleic Acids Res       Date:  2007-12-01       Impact factor: 16.971

  7 in total

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