Mod/Resc Parsimony Inference: Theory and application

  • Authors:

  • Igor Nor;Danny Hermelin;Sylvain Charlat;Jan Engelstadter;Max Reuter;Olivier Duron;Marie-France Sagot

  • Affiliations:

  • Université de Lyon, F-69000, Lyon, Université Lyon 1, CNRS, UMR5558, France and Bamboo Team, INRIA Grenoble Rhône-Alpes, France;Max Planck Institute for Informatics, Saarbrücken, Germany;Université de Lyon, F-69000, Lyon, Université Lyon 1, CNRS, UMR5558, France;Institute of Integrative Biology, ETH Zurich, Switzerland;University College London, UK;Institute of Evolutionary Sciences, CNRS - University of Montpellier II, France;Université de Lyon, F-69000, Lyon, Université Lyon 1, CNRS, UMR5558, France and Bamboo Team, INRIA Grenoble Rhône-Alpes, France

  • Venue:
  • Information and Computation
  • Year:
  • 2012

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Abstract

We address in this paper a new computational biology problem that aims at understanding a mechanism that could potentially be used to genetically manipulate natural insect populations infected by inherited, intra-cellular parasitic bacteria. In this problem, that we denote by Mod/Resc Parsimony Inference, we are given a boolean matrix and the goal is to find two other boolean matrices with a minimum number of columns such that an appropriately defined operation on these matrices gives back the input. We show that this is formally equivalent to the Biclique Edge Cover for Bipartite Graphs problem and derive some complexity results for our problem using this equivalence. We provide a new, fixed-parameter tractability approach for solving both problems that slightly improves upon a previously published algorithm for the Biclique Edge Cover for Bipartite Graphs. Finally, we present experimental results applying some of our techniques to a real-life dataset.