Literature DB >> 16922695

Analysis and comparison of benchmarks for multiple sequence alignment.

Gordon Blackshields1, Iain M Wallace, Mark Larkin, Desmond G Higgins.   

Abstract

The most popular way of comparing the performance of multiple sequence alignment programs is to use empirical testing on sets of test sequences. Several such test sets now exist, each with potential strengths and weaknesses. We apply several different alignment packages to 6 benchmark datasets, and compare their relative performances. HOMSTRAD, a collection of alignments of homologous proteins, is regularly used as a benchmark for sequence alignment though it is not designed as such, and lacks annotation of reliable regions within the alignment. We introduce this annotation into HOMSTRAD using protein structural superposition. Results on each database show that method performance is dependent on the input sequences. Alignment benchmarks are regularly used in combination to measure performance across a spectrum of alignment problems. Through combining benchmarks, it is possible to detect whether a program has been over-optimised for a single dataset, or alignment problem type.

Mesh:

Year:  2006        PMID: 16922695

Source DB:  PubMed          Journal:  In Silico Biol        ISSN: 1386-6338


  25 in total

1.  MTRAP: pairwise sequence alignment algorithm by a new measure based on transition probability between two consecutive pairs of residues.

Authors:  Toshihide Hara; Keiko Sato; Masanori Ohya
Journal:  BMC Bioinformatics       Date:  2010-05-08       Impact factor: 3.169

2.  BCL::Align-sequence alignment and fold recognition with a custom scoring function online.

Authors:  Elizabeth Dong; Jarrod Smith; Sten Heinze; Nathan Alexander; Jens Meiler
Journal:  Gene       Date:  2008-06-07       Impact factor: 3.688

3.  Multiple Sequence Alignment Averaging Improves Phylogeny Reconstruction.

Authors:  Haim Ashkenazy; Itamar Sela; Eli Levy Karin; Giddy Landan; Tal Pupko
Journal:  Syst Biol       Date:  2019-01-01       Impact factor: 15.683

4.  Evaluating Statistical Multiple Sequence Alignment in Comparison to Other Alignment Methods on Protein Data Sets.

Authors:  Michael Nute; Ehsan Saleh; Tandy Warnow
Journal:  Syst Biol       Date:  2019-05-01       Impact factor: 15.683

5.  Jalview Version 2--a multiple sequence alignment editor and analysis workbench.

Authors:  Andrew M Waterhouse; James B Procter; David M A Martin; Michèle Clamp; Geoffrey J Barton
Journal:  Bioinformatics       Date:  2009-01-16       Impact factor: 6.937

6.  Phylogenetic assessment of alignments reveals neglected tree signal in gaps.

Authors:  Christophe Dessimoz; Manuel Gil
Journal:  Genome Biol       Date:  2010-04-06       Impact factor: 13.583

Review 7.  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 8.  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

9.  Optimizing substitution matrix choice and gap parameters for sequence alignment.

Authors:  Robert C Edgar
Journal:  BMC Bioinformatics       Date:  2009-12-02       Impact factor: 3.169

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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