A word-oriented approach to alignment validation.

Robert G Beiko; Cheong Xin Chan; Mark A Ragan

doi:10.1093/bioinformatics/bti335

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A word-oriented approach to alignment validation.

Robert G Beiko·Cheong Xin Chan·Mark A Ragan

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Abstract

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.

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Algorithms Artificial Intelligence Natural Language Processing Pattern Recognition, Automated Proteins Semantics Sequence Alignment Sequence Analysis, Protein Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study

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Robert G Beiko, Cheong Xin Chan, Mark A Ragan. 2005-02-22. A word-oriented approach to alignment validation.. https://doi.org/10.1093/bioinformatics%2Fbti335

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