An enhanced genetic algorithm for DNA sequencing by hybridization with positive and negative errors

Thang N. Bui, Waleed A. Youssef

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Scopus citations

Abstract

This paper describes a genetic algorithm for the DNA sequencing problem. The algorithm allows the input spectrum to contain both positive and negative errors as could be expected from a hybridization experiment. The main features of the algorithm include a preprocessing step that reduces the size of the input spectrum and an efficient local optimization. In experimental tests, the algorithm performed very well against existing algorithms. The algorithm also performed very well on a large data set generated in this paper from real genomes data.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsRiccardo Poli, Owen Holland, Wolfgang Banzhaf, Hans-Georg Beyer, Edmund Burke, Paul Darwen, Dipankar Dasgupta, Dario Floreano, James Foster, Mark Harman, Pier Luca Lanzi, Lee Spector, Andrea G. B. Tettamanzi, Dirk Thierens, Andrew M. Tyrrell
PublisherSpringer Verlag
Pages908-919
Number of pages12
ISBN (Print)3540223436
DOIs
StatePublished - Jan 1 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3103
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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