Algorithms in Bioinformatics

Volume 4175 of the series Lecture Notes in Computer Science pp 344-354

A Linear-Time Algorithm for Studying Genetic Variation

  • Nikola StojanovicAffiliated withDepartment of Computer Science and Engineering, The University of Texas at Arlington
  • , Piotr BermanAffiliated withDepartment of Computer Science and Engineering, The Pennsylvania State University

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The study of variation in DNA sequences, within the framework of phylogeny or population genetics, for instance, is one of the most important subjects in modern genomics. We here present a new linear-time algorithm for finding maximal k-regions in alignments of three sequences, which can be used for the detection of segments featuring a certain degree of similarity, as well as the boundaries of distinct genomic environments such as gene clusters or haplotype blocks. k-regions are defined as these which have a center sequence whose Hamming distance from any of the alignment rows is at most k, and their determination in the general case is known to be NP-hard.