An improved satisfiability algorithm for nested canalyzing functions and its application to determining a singleton attractor of a boolean network

Avraham A. Melkman, Tatsuya Akutsu

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We study the problem of finding a 0-1 assignment to Boolean variables satisfying a given set of nested canalyzing functions, a class of Boolean functions that is known to be of interest in biology. For this problem, an extension of the satisfiability problem for a conjunctive normal form formula, an O(min(2k, 2(k+m)/2)poly(m)) time algorithm has been known, where m and k are the number of nested canalyzing functions and variables, respectively. Here we present an improved O(min(2k, 1.325k+m, 2m)poly(m)) time algorithm for this problem. We also study the problem of finding a singleton attractor of a Boolean network consisting of n nested canalyzing functions. Although an O(1.799n) time algorithm was proposed in a previous study, it was implicitly assumed that the network does not contain any positive self-loops. By utilizing the improved satisfiability algorithm for nested canalyzing functions, while allowing for the presence of positive self-loops, we show that the general case can be solved in O(1.871n) time.

Original languageEnglish
Pages (from-to)958-969
Number of pages12
JournalJournal of Computational Biology
Volume20
Issue number12
DOIs
StatePublished - 1 Dec 2013

Keywords

  • Boolean network
  • SAT
  • nested canalyzing function.
  • singleton attractor

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

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