• DocumentCode
    478586
  • Title

    Haplotype Inference with Boolean Constraint Solving: An Overview

  • Author

    Lynce, Inês ; Graca, A. ; Marques-Silva, João ; Oliveira, Arlindo L.

  • Author_Institution
    IST/INESC-ID, TU, Lisbon
  • Volume
    1
  • fYear
    2008
  • fDate
    3-5 Nov. 2008
  • Firstpage
    92
  • Lastpage
    100
  • Abstract
    Boolean satisfiability (SAT) finds a wide range of practical applications, including Artificial Intelligence and, more recently, Bioinformatics. Although encoding some combinatorial problems using Boolean logic may not be the most intuitive solution, the efficiency of state-of-the-art SAT solvers often makes it worthwhile to consider encoding a problem to SAT. One representative application of SAT in Bioinformatics is haplotype inference. The problem of haplotype inference under the assumption of pure parsimony consists in finding the smallest number of haplotypes that explains a given set of genotypes. The original formulations for solving the problem of Haplotype Inference by Pure Parsimony (HIPP) were based on Integer Linear Programming. More recently, solutions based on SAT have been shown to be remarkably more efficient. This paper provides an overview of SAT-based approaches for solving the HIPP problem and identifies current research directions.
  • Keywords
    Boolean functions; artificial intelligence; bioinformatics; inference mechanisms; integer programming; linear programming; Boolean constraint; Boolean logic; Boolean satisfiability; SAT; artificial intelligence; bioinformatics; combinatorial problems; haplotype inference; integer linear programming; pure parsimony; Artificial intelligence; Bioinformatics; DNA; Diseases; Encoding; Genetic mutations; Humans; Integer linear programming; Organisms; Sequences; Boolean Constraint Solving; Haplotype Inference;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2008. ICTAI '08. 20th IEEE International Conference on
  • Conference_Location
    Dayton, OH
  • ISSN
    1082-3409
  • Print_ISBN
    978-0-7695-3440-4
  • Type

    conf

  • DOI
    10.1109/ICTAI.2008.135
  • Filename
    4669676