An algorithm for approximate tandem repeats

G. M. Landau, J. P. Schmidt, D. Sokol

Research output: Contribution to journalArticlepeer-review


A perfect single tandem repeat is defined as a nonempty string that can be divided into two identical substrings, e.g., abcabc. An approximate single tandem repeat is one in which the substrings are similar, but not identical, e.g., abcdaacd. In this paper we consider two criterions of similarity: the Hamming distance (k mismatches) and the edit distance (k differences). For a string S of length n and an integer k our algorithm reports all locally optimal approximate repeats, r = ūû, for which the Hamming distance of ū and û is at most k, in O (nk log(n/ k)) time, or all those for which the edit distance of ū and û is at most k, in O (nk log k log(n/ k)) time. This paper concentrates on a more general type of repeat called multiple tandem repeats. A multiple tandem repeat in a sequence S is a (periodic) substring r of S of the form r = uau′, where u is a prefix of r and u′ is a prefix of u. An approximate multiple tandem repeat is a multiple repeat with errors; the repeated subsequences are similar but not identical. We precisely define approximate multiple repeats, and present an algorithm that finds all repeats that concur with our definition. The time complexity of the algorithm, when searching for repeats with up to k errors in a string S of length n, is O (nka log(n/ k)) where a is the maximum number of periods in any reported repeat. We present some experimental results concerning the performance and sensitivity of our algorithm. The problem of finding repeats within a string is a computational problem with important applications in the field of molecular biology. Both exact and inexact repeats occur frequently in the genome, and certain repeats occurring in the genome are known to be related to diseases in the human.

Original languageEnglish
Pages (from-to)1-18
Number of pages18
JournalJournal of Computational Biology
Issue number1
StatePublished - 2001

ASJC Scopus subject areas

  • Computational Mathematics
  • Genetics
  • Molecular Biology
  • Computational Theory and Mathematics
  • Modeling and Simulation


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