A unifying framework for seed sensitivity and its application to subset seeds

Details A unifying framework for seed sensitivity and its application to subset seeds A unifying framework for seed sensitivity and its application to subset seeds

2006-01-27

arxiv.org/abs/cs/0601116v2

Journal of Bioinformatics and Computational Biology 4 (2006) 2, pp 553--569

Computer Science

Data Structures and Algorithms

Scientific paper

10.1142/S0219720006001977

We propose a general approach to compute the seed sensitivity, that can be applied to different definitions of seeds. It treats separately three components of the seed sensitivity problem -- a set of target alignments, an associated probability distribution, and a seed model -- that are specified by distinct finite automata. The approach is then applied to a new concept of subset seeds for which we propose an efficient automaton construction. Experimental results confirm that sensitive subset seeds can be efficiently designed using our approach, and can then be used in similarity search producing better results than ordinary spaced seeds.

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