Literature DB >> 3806669

Multiple sequence alignment.

D J Bacon, W F Anderson.   

Abstract

A method has been developed for aligning segments of several sequences at once. The number of search steps depends only polynomially on the number of sequences, instead of exponentially, because most alignments are rejected without being evaluated explicitly. A data structure herein called the "heap" facilitates this process. For a set of n sequence segments, the overall similarity is taken to be the sum of all the constituent segment pair similarities, which are in turn sums of corresponding residue similarity scores from a Table. The statistical models that test alignments for significance make it possible to group sequences objectively, even when most or all of the interrelationships are weak. These tests are very sensitive, while remaining quite conservative, and discourage the addition of "misfit" sequences to an existing set. The new techniques are applied to a set of five DNA-binding proteins, to a group of three enzymes that employ the coenzyme FAD, and to a control set. The alignment previously proposed for the DNA-binding proteins on the basis of structural comparisons and inspection of sequences is supported quite dramatically, and a highly significant alignment is found for the FAD-binding proteins.

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Year:  1986        PMID: 3806669     DOI: 10.1016/0022-2836(86)90252-4

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  27 in total

1.  TBC: a clustering algorithm based on prokaryotic taxonomy.

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Journal:  J Microbiol       Date:  2012-04-27       Impact factor: 3.422

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.  Compositional adjustment of Dirichlet mixture priors.

Authors:  Xugang Ye; Yi-Kuo Yu; Stephen F Altschul
Journal:  J Comput Biol       Date:  2010-12       Impact factor: 1.479

4.  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

5.  A comparison of several similarity indices used in the classification of protein sequences: a multivariate analysis.

Authors:  C Landès; A Hénaut; J L Risler
Journal:  Nucleic Acids Res       Date:  1992-07-25       Impact factor: 16.971

6.  An efficient algorithm for identifying matches with errors in multiple long molecular sequences.

Authors:  M Y Leung; B E Blaisdell; C Burge; S Karlin
Journal:  J Mol Biol       Date:  1991-10-20       Impact factor: 5.469

7.  Modelling of peptide and protein structures.

Authors:  S Fraga; J M Parker
Journal:  Amino Acids       Date:  1994-06       Impact factor: 3.520

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

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

9.  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

10.  Self-organizing hierarchic networks for pattern recognition in protein sequence.

Authors:  J Hanke; G Beckmann; P Bork; J G Reich
Journal:  Protein Sci       Date:  1996-01       Impact factor: 6.725

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