Designing multiple simultaneous seeds for DNA similarity search

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

32 Scopus Citations
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Original languageEnglish
Pages (from-to)847-861
Journal / PublicationJournal of Computational Biology
Issue number6
Publication statusPublished - Jul 2005
Externally publishedYes


The challenge of similarity search in massive DNA sequence databases has inspired major changes in BLAST-style alignment tools, which accelerate search by inspecting only pairs of sequences sharing a common short "seed," or pattern of matching residues. Some of these changes raise the possibility of improving search performance by probing sequence pairs with several distinct seeds, any one of which is sufficient for a seed match. However, designing a set of seeds to maximize their combined sensitivity to biologically meaningful sequence alignments is computationally difficult, even given recent advances in designing single seeds. This work describes algorithmic improvements to seed design that address the problem of designing a set of n seeds to be used simultaneously. We give a new local search method to optimize the sensitivity of seed sets. The method relies on efficient incremental computation of the probability that an alignment contains a match to a seed π, given that it has already failed to match any of the seeds in a set Π. We demonstrate experimentally that multi-seed designs, even with relatively few seeds, can be significantly more sensitive than even optimized single-seed designs. © Mary Ann Liebert, Inc.

Research Area(s)

  • Database search, DNA sequence comparison, Mandala, Seed design, Sequence alignment

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