Literature DB >> 2706401

Approximate matching of regular expressions.

E W Myers, W Miller.   

Abstract

Given a sequence A and regular expression R, the approximate regular expression matching problem is to find a sequence matching R whose optimal alignment with A is the highest scoring of all such sequences. This paper develops an algorithm to solve the problem in time O(MN), where M and N are the lengths of A and R. Thus, the time requirement is asymptotically no worse than for the simpler problem of aligning two fixed sequences. Our method is superior to an earlier algorithm by Wagner and Seiferas in several ways. First, it treats real-valued costs, in addition to integer costs, with no loss of asymptotic efficiency. Second, it requires only O(N) space to deliver just the score of the best alignment. Finally, its structure permits implementation techniques that make it extremely fast in practice. We extend the method to accommodate gap penalties, as required for typical applications in molecular biology, and further refine it to search for sub-strings of A that strongly align with a sequence in R, as required for typical data base searches. We also show how to deliver an optimal alignment between A and R in only O(N + log M) space using O(MN log M) time. Finally, an O(MN(M + N) + N2log N) time algorithm is presented for alignment scoring schemes where the cost of a gap is an arbitrary increasing function of its length.

Mesh:

Year:  1989        PMID: 2706401     DOI: 10.1007/BF02458834

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  6 in total

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2.  Turn prediction in proteins using a pattern-matching approach.

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3.  Optimal alignments in linear space.

Authors:  E W Myers; W Miller
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4.  Sequence comparison with concave weighting functions.

Authors:  W Miller; E W Myers
Journal:  Bull Math Biol       Date:  1988       Impact factor: 1.758

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Authors:  R M Abarbanel; P R Wieneke; E Mansfield; D A Jaffe; D L Brutlag
Journal:  Nucleic Acids Res       Date:  1984-01-11       Impact factor: 16.971

6.  An improved algorithm for matching biological sequences.

Authors:  O Gotoh
Journal:  J Mol Biol       Date:  1982-12-15       Impact factor: 5.469

  6 in total
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