Literature DB >> 17237099

Multiple alignment by sequence annealing.

Ariel S Schwartz1, Lior Pachter.   

Abstract

MOTIVATION: We introduce a novel approach to multiple alignment that is based on an algorithm for rapidly checking whether single matches are consistent with a partial multiple alignment. This leads to a sequence annealing algorithm, which is an incremental method for building multiple sequence alignments one match at a time. Our approach improves significantly on the standard progressive alignment approach to multiple alignment.
RESULTS: The sequence annealing algorithm performs well on benchmark test sets of protein sequences. It is not only sensitive, but also specific, drastically reducing the number of incorrectly aligned residues in comparison to other programs. The method allows for adjustment of the sensitivity/specificity tradeoff and can be used to reliably identify homologous regions among protein sequences. AVAILABILITY: An implementation of the sequence annealing algorithm is available at http://bio.math.berkeley.edu/amap/

Mesh:

Substances:

Year:  2007        PMID: 17237099     DOI: 10.1093/bioinformatics/btl311

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  30 in total

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2.  Specific alignment of structured RNA: stochastic grammars and sequence annealing.

Authors:  Robert K Bradley; Lior Pachter; Ian Holmes
Journal:  Bioinformatics       Date:  2008-09-16       Impact factor: 6.937

3.  The promoter of a gene encoding an isoflavone reductase-like protein in coffee (Coffea arabica) drives a stress-responsive expression in leaves.

Authors:  Marcos Brandalise; Fabio E Severino; Mirian P Maluf; Ivan G Maia
Journal:  Plant Cell Rep       Date:  2009-09-16       Impact factor: 4.570

4.  Cactus: Algorithms for genome multiple sequence alignment.

Authors:  Benedict Paten; Dent Earl; Ngan Nguyen; Mark Diekhans; Daniel Zerbino; David Haussler
Journal:  Genome Res       Date:  2011-06-10       Impact factor: 9.043

5.  High sensitivity to aligner and high rate of false positives in the estimates of positive selection in the 12 Drosophila genomes.

Authors:  Penka Markova-Raina; Dmitri Petrov
Journal:  Genome Res       Date:  2011-03-10       Impact factor: 9.043

6.  Evolutionary inference via the Poisson Indel Process.

Authors:  Alexandre Bouchard-Côté; Michael I Jordan
Journal:  Proc Natl Acad Sci U S A       Date:  2012-12-28       Impact factor: 11.205

7.  Evolution, biogenesis, expression, and target predictions of a substantially expanded set of Drosophila microRNAs.

Authors:  J Graham Ruby; Alexander Stark; Wendy K Johnston; Manolis Kellis; David P Bartel; Eric C Lai
Journal:  Genome Res       Date:  2007-11-07       Impact factor: 9.043

8.  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

9.  PicXAA: greedy probabilistic construction of maximum expected accuracy alignment of multiple sequences.

Authors:  Sayed Mohammad Ebrahim Sahraeian; Byung-Jun Yoon
Journal:  Nucleic Acids Res       Date:  2010-04-22       Impact factor: 16.971

10.  Evolutionary triplet models of structured RNA.

Authors:  Robert K Bradley; Ian Holmes
Journal:  PLoS Comput Biol       Date:  2009-08-28       Impact factor: 4.475

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