A polynomial time equivalence between DNA sequencing and the exact perfect matching problem

  • Authors:

  • Jacek BłAewicz;Piotr Formanowicz;Marta Kasprzak;Petra Schuurman;Gerhard J. Woeginger

  • Affiliations:

  • Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland and Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, ...;Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland and Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, ...;Institute of Computing Science, Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland and Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, ...;Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, NL-5600 MB Eindhoven, The Netherlands;Department of Mathematics and Computer Science, Eindhoven University of Technology, P.O. Box 513, NL-5600 MB Eindhoven, The Netherlands

  • Venue:
  • Discrete Optimization
  • Year:
  • 2007

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Abstract

We investigate the computational complexity of a combinatorial problem that arises in DNA sequencing by hybridization: The input consists of an integer @? together with a set S of words of length k over the four symbols A, C, G, T. The problem is to decide whether there exists a word of length @? that contains every word in S at least once as a subword, and does not contain any other subword of length k. The computational complexity of this problem has been open for some time, and it remains open. What we prove is that this problem is polynomial time equivalent to the exact perfect matching problem in bipartite graphs, which is another infamous combinatorial optimization problem of unknown computational complexity.