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Bioinformatics Advance Access originally published online on February 22, 2005
Bioinformatics 2005 21(10):2230-2239; doi:10.1093/bioinformatics/bti335
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

A word-oriented approach to alignment validation

Robert G. Beiko , Cheong Xin Chan and Mark A. Ragan *

ARC Centre in Bioinformatics and Institute for Molecular Bioscience, The University of Queensland Brisbane, Qld 4072, Australia

*To whom correspondence should be addressed.

Motivation: Multiple sequence alignment at the level of whole proteomes requires a high degree of automation, precluding the use of traditional validation methods such as manual curation. Since evolutionary models are too general to describe the history of each residue in a protein family, there is no single algorithm/model combination that can yield a biologically or evolutionarily optimal alignment. We propose a ‘shotgun’ strategy where many different algorithms are used to align the same family, and the best of these alignments is then chosen with a reliable objective function. We present WOOF, a novel ‘word-oriented’ objective function that relies on the identification and scoring of conserved amino acid patterns (words) between pairs of sequences.

Results: Tests on a subset of reference protein alignments from BAliBASE showed that WOOF tended to rank the (manually curated) reference alignment highest among 1060 alternative (automatically generated) alignments for a majority of protein families. Among the automated alignments, there was a strong positive relationship between the WOOF score and similarity to the reference alignment. The speed of WOOF and its independence from explicit considerations of three-dimensional structure make it an excellent tool for analyzing large numbers of protein families.

Availability: On request from the authors.

Contact: m.ragan{at}imb.uq.edu.au


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