Literature DB >> 8654965

A general method for fast multiple sequence alignment.

U Tönges1, S W Perrey, J Stoye, A W Dress.   

Abstract

We have developed a fast heuristic algorithm for multiple sequence alignment which provides near-to-optimal results for sufficiently homologous sequences. The algorithm makes use of the standard dynamic programming procedure by applying it to all pairs of sequences. The resulting score matrices for pair-wise alignment give rise to secondary matrices containing the additional charges imposed by forcing the alignment path to run through a particular vertex. Such a constraint corresponds to slicing the sequences at the positions defining that vertex, and aligning the remaining pairs of prefix and suffix sequences separately. From these secondary matrices, one can compute-for any given family of sequences-suitable positions for cutting all of these sequences simultaneously, thus reducing the problem of aligning a family of n sequences of average length l in a Divide and Conquer fashion to aligning two families of n sequences of approximately half that length. In this paper, we explain the method for the case of 3 sequences in detail, and we demonstrate its potential and its limits by discussing its behaviour for several test families. A generalization for aligning more than 3 sequences is lined out, and some actual alignments constructed by our algorithm for various user-defined parameters are presented.

Mesh:

Year:  1996        PMID: 8654965     DOI: 10.1016/0378-1119(96)00123-0

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  6 in total

1.  A memory-efficient algorithm for multiple sequence alignment with constraints.

Authors:  Chin Lung Lu; Yen Pin Huang
Journal:  Bioinformatics       Date:  2004-09-16       Impact factor: 6.937

2.  MCALIGN: stochastic alignment of noncoding DNA sequences based on an evolutionary model of sequence evolution.

Authors:  Peter D Keightley; Toby Johnson
Journal:  Genome Res       Date:  2004-03       Impact factor: 9.043

3.  Dynamic programming algorithms for comparing multineuronal spike trains via cost-based metrics and alignments.

Authors:  Jonathan D Victor; David H Goldberg; Daniel Gardner
Journal:  J Neurosci Methods       Date:  2006-12-15       Impact factor: 2.390

4.  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

5.  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

6.  Detailed protein sequence alignment based on Spectral Similarity Score (SSS).

Authors:  Kshitiz Gupta; Dina Thomas; S V Vidya; K V Venkatesh; S Ramakumar
Journal:  BMC Bioinformatics       Date:  2005-04-23       Impact factor: 3.169

  6 in total

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