A time-efficient, linear-space local similarity algorithm

Authors:
Xiaoqiu Huang;Webb Miller
Affiliations:
Department of Computer Science, Michigan Technological University, Houghton, Michigan 49931 U.S.A.;Department of Computer Science, The Pennsylvania State University, University Park, Pennsylvania 16802 U.S.A.
Venue:
Advances in Applied Mathematics
Year:
1991

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Abstract

Dynamic programming algorithms to determine similar regions of two sequences are useful for analyzing biosequence data. This paper presents a time-efficient algorithm that produces k best ''non-intersecting'' local alignments for any chosen k. The algorithm's main strength is that it needs only O(M + N + K) space, where M and N are the lengths of the given sequences and K is the total length of the computed alignments.