A Novel Heuristic for Local Multiple Alignment of Interspersed DNA Repeats
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Assessing the Discordance of Multiple Sequence Alignments
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Gapped extension for local multiple alignment of interspersed DNA repeats
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Procrastination leads to efficient filtration for local multiple alignment
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Computational molecular biology of genome expression and regulation
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
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Summary: BLAST statistics have been shown to be extremely useful for searching for significant similarity hits, for amino acid and nucleotide sequences. Although these statistics are well understood for pairwise comparisons, there has been little success developing statistical scores for multiple alignments. In particular, there is no score for multiple alignment that is well founded and treated as a standard. We extend the BLAST theory to multiple alignments. Following some simple assumptions, we present and justify a significance score for multiple segments of a local multiple alignment. We demonstrate its usefulness in distinguishing high and moderate quality multiple alignments from low quality ones, with supporting experiments on orthologous vertebrate promoter sequences. Contact: amol@cs.washington.edu