Sparse normalized local alignment

Nadav Efraty, Gad M. Landau

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Given two strings, X and Y, both of length O(n) over alphabet ∑, a basic problem (local alignment) is to find pairs of similar substrings, one from X and one from Y. For substrings X' and Y' from X and Y, respectively, the metric we use to measure their similarity is normalized alignment value: LCS(X', Y')/(|X'| + |Y'|). Given an integer M we consider only those substrings whose LCS length is at least M. We present an algorithm that reports the pairs of substrings with the highest normalized alignment value in O(n log |∑| + r M log log n) time (r - the number of matches between X and Y). We also present an O(n log |∑| + r L log log n) algorithm (L = LCS(X, Y)) that reports all substring pairs with a normalized alignment value above a given threshold.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsSuleyman Cenk Sahinalp, S. Muthukrishnan, Ugur Dogrusoz
PublisherSpringer Verlag
Pages333-346
Number of pages14
ISBN (Print)354022341X, 9783540223412
DOIs
StatePublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3109
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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