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Efficient Computation of Long Similar Subsequences

Abdullah N. ArslanContact Information and Ömer EğecioğluContact Information

(6)  Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA 93106, USA
Abstract
Given sequences X of length n and Y of length m with nm, let LAt* and NLAt* denote the maximum ordinary, and maximum length normalized scores of local alignments with length at least a given threshold value t. The alignment length is defined as the sum of the lengths of the involved subsequences, and length normalized score of an alignment is the quotient of the ordinary score by the alignment length. We develop an algorithm which finds an alignment with ordinary score ≥ LAt*, and length ≥ (1 - 1/r)t for a given r, in time O(rnm) and space O(rm). The algorithm can be used to find an alignment with length normalized score > λ for a given positive λ with the same time and space complexity and within the same approximation bounds. Thus this algorithm provides a length-approximate answer to a query such as “Do X and Y share a (sufficiently long) fragment with more than 70% of similarity?” We also show that our approach gives improved approximation algorithms for the normalized local alignment problem. In this case we can efficiently find an alignment with length ≥ (1 - 1/r)t which has a length normalized score ≥ NLAt*.

Keywords  Local alignment - normalized local alignment - approximation algorithm - dynamic programming - ratio maximization

Supported in part by NSF Grants No. CCR-9821038 and No. EIA-9818320.

Contact Information Abdullah N. Arslan
Email: arslan@cs.ucsb.edu

Contact Information Ömer Eğecioğlu
Email: omer@cs.ucsb.edu
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