Prof. Avraham Melkman

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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

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.

Publication language English
Pages 958-969
Journal Journal of Computational Biology
Volume 20
Issue number 12
Publication status Published - 01.12.2013

Keywords

Boolean network
nested canalyzing function.
SAT
singleton attractor

ASJC Scopus subject areas

Modeling and Simulation
Molecular Biology
Genetics
Computational Mathematics
Computational Theory and Mathematics
Access to Document
10.1089/cmb.2013.0060
Other files and links
Link to publication in Scopus