Literature DB >> 8078398

Comparative analysis of multiple protein-sequence alignment methods.

M A McClure1, T K Vasi, W M Fitch.   

Abstract

We have analyzed a total of 12 different global and local multiple protein-sequence alignment methods. The purpose of this study is to evaluate each method's ability to correctly identify the ordered series of motifs found among all members of a given protein family. Four phylogenetically distributed sets of sequences from the hemoglobin, kinase, aspartic acid protease, and ribonuclease H protein families were used to test the methods. The performance of all 12 methods was affected by (1) the number of sequences in the test sets, (2) the degree of similarity among the sequences, and (3) the number of indels required to produce a multiple alignment. Global methods generally performed better than local methods in the detection of motif patterns.

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Year:  1994        PMID: 8078398     DOI: 10.1093/oxfordjournals.molbev.a040138

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  19 in total

1.  Molecular identification of enterovirus by analyzing a partial VP1 genomic region with different methods.

Authors:  G Palacios; I Casas; A Tenorio; C Freire
Journal:  J Clin Microbiol       Date:  2002-01       Impact factor: 5.948

2.  MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

Authors:  Kazutaka Katoh; Kazuharu Misawa; Kei-ichi Kuma; Takashi Miyata
Journal:  Nucleic Acids Res       Date:  2002-07-15       Impact factor: 16.971

3.  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

4.  A non-local gap-penalty for profile alignment.

Authors:  W R Taylor
Journal:  Bull Math Biol       Date:  1996-01       Impact factor: 1.758

5.  Multiple DNA and protein sequence alignment based on segment-to-segment comparison.

Authors:  B Morgenstern; A Dress; T Werner
Journal:  Proc Natl Acad Sci U S A       Date:  1996-10-29       Impact factor: 11.205

6.  Modeling sequence and function similarity between proteins for protein functional annotation.

Authors:  Roger Higdon; Brenton Louie; Eugene Kolker
Journal:  Proc Int Symp High Perform Distrib Comput       Date:  2010

7.  The size distribution of insertions and deletions in human and rodent pseudogenes suggests the logarithmic gap penalty for sequence alignment.

Authors:  X Gu; W H Li
Journal:  J Mol Evol       Date:  1995-04       Impact factor: 2.395

Review 8.  Issues in bioinformatics benchmarking: the case study of multiple sequence alignment.

Authors:  Mohamed Radhouene Aniba; Olivier Poch; Julie D Thompson
Journal:  Nucleic Acids Res       Date:  2010-07-17       Impact factor: 16.971

Review 9.  Upcoming challenges for multiple sequence alignment methods in the high-throughput era.

Authors:  Carsten Kemena; Cedric Notredame
Journal:  Bioinformatics       Date:  2009-07-30       Impact factor: 6.937

10.  Quality measures for protein alignment benchmarks.

Authors:  Robert C Edgar
Journal:  Nucleic Acids Res       Date:  2010-01-04       Impact factor: 16.971

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