Computing Alignment Seed Sensitivity with Probabilistic Arithmetic Automata
WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
Detecting fuzzy amino acid tandem repeats in protein sequences
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
AcoSeeD: an ant colony optimization for finding optimal spaced seeds in biological sequence search
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
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Motivation: Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. The introduction of optimal spaced seeds in PatternHunter has increased both the sensitivity and the speed of homology search, and it has been adopted by many alignment programs such as BLAST. With the further improvement provided by multiple spaced seeds in PatternHunterII, Smith–Waterman sensitivity is approached at BLASTn speed. However, computing optimal multiple spaced seeds was proved to be NP-hard and current heuristic algorithms are all very slow (exponential). Results: We give a simple algorithm which computes good multiple seeds in polynomial time. Due to a completely different approach, the difference with respect to the previous methods is dramatic. The multiple spaced seed of PatternHunterII, with 16 weight 11 seeds, was computed in 12 days. It takes us 17 s to find a better one. Our approach changes the way of looking at multiple spaced seeds. Contact: ilie@csd.uwo.ca