Literature DB >> 2593679

Gap costs for multiple sequence alignment.

S F Altschul1.   

Abstract

Standard methods for aligning pairs of biological sequences charge for the most common mutations, which are substitutions, deletions and insertions. Because a single mutation may insert or delete several nucleotides, gap costs that are not directly proportional to gap length are usually the most effective. How to extend such gap costs to alignments of three or more sequences is not immediately obvious, and a variety of approaches have been taken. This paper argues that, since gap and substitution costs together specify optimal alignments, they should be defined using a common rationale. Specifically, a new definition of gap costs for multiple alignments is proposed and compared with previous ones. Since the new definition links a multiple alignment's cost to that of its pairwise projections, it allows knowledge gained about two-sequence alignments to bear on the multiple alignment problem. Also, such linkage is a key element of recent algorithms that have rendered practical the simultaneous alignment of as many as six sequences.

Mesh:

Year:  1989        PMID: 2593679     DOI: 10.1016/s0022-5193(89)80196-1

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  17 in total

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Authors:  Scott Schwartz; Laura Elnitski; Mei Li; Matt Weirauch; Cathy Riemer; Arian Smit; Eric D Green; Ross C Hardison; Webb Miller
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

2.  An assessment of substitution scores for protein profile-profile comparison.

Authors:  Xugang Ye; Guoli Wang; Stephen F Altschul
Journal:  Bioinformatics       Date:  2011-10-13       Impact factor: 6.937

3.  A survey of multiple sequence comparison methods.

Authors:  S C Chan; A K Wong; D K Chiu
Journal:  Bull Math Biol       Date:  1992-07       Impact factor: 1.758

4.  Mind the gaps: progress in progressive alignment.

Authors:  D G Higgins; G Blackshields; I M Wallace
Journal:  Proc Natl Acad Sci U S A       Date:  2005-07-18       Impact factor: 11.205

5.  Multiple sequence alignment by conformational space annealing.

Authors:  Keehyoung Joo; Jinwoo Lee; Ilsoo Kim; Sung Jong Lee; Jooyoung Lee
Journal:  Biophys J       Date:  2008-08-08       Impact factor: 4.033

6.  Efficient methods for multiple sequence alignment with guaranteed error bounds.

Authors:  D Gusfield
Journal:  Bull Math Biol       Date:  1993-01       Impact factor: 1.758

7.  A multiple sequence comparison method.

Authors:  A K Wong; S C Chan; D K Chiu
Journal:  Bull Math Biol       Date:  1993-03       Impact factor: 1.758

8.  SAGA: sequence alignment by genetic algorithm.

Authors:  C Notredame; D G Higgins
Journal:  Nucleic Acids Res       Date:  1996-04-15       Impact factor: 16.971

9.  Sequence Comparison Without Alignment: The SpaM Approaches.

Authors:  Burkhard Morgenstern
Journal:  Methods Mol Biol       Date:  2021

10.  The construction and use of log-odds substitution scores for multiple sequence alignment.

Authors:  Stephen F Altschul; John C Wootton; Elena Zaslavsky; Yi-Kuo Yu
Journal:  PLoS Comput Biol       Date:  2010-07-15       Impact factor: 4.475

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