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Inference of Boolean Networks from Gene Interaction Graphs Using a SAT Solver

  • David A. Rosenblueth
  • Stalin Muñoz
  • Miguel Carrillo
  • Eugenio Azpeitia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8542)

Abstract

Boolean networks are important models of gene regulatory networks. Such models are sometimes built from: (1) a gene interaction graph and (2) a set of biological constraints. A gene interaction graph is a directed graph representing positive and negative gene regulations. Depending on the biological problem being solved, the set of biological constraints can vary, and may include, for example, a desired set of stationary states. We present a symbolic, SAT-based, method for inferring synchronous Boolean networks from interaction graphs augmented with constraints. Our method first constructs Boolean formulas in such a way that each truth assignment satisfying these formulas corresponds to a Boolean network modeling the given information. Next, we employ a SAT solver to obtain desired Boolean networks. Through a prototype, we show results illustrating the use of our method in the analysis of Boolean gene regulatory networks of the Arabidopsis thaliana root stem cell niche.

Keywords

Boolean network Gene interaction graph SAT solver 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • David A. Rosenblueth
    • 1
    • 3
  • Stalin Muñoz
    • 1
  • Miguel Carrillo
    • 1
  • Eugenio Azpeitia
    • 2
    • 3
  1. 1.Instituto de Investigaciones en Matemáticas Aplicadas y en SistemasUniversidad Nacional Autónoma de MéxicoMéxico, D.F.México
  2. 2.Laboratorio de Genética Molecular, Desarrollo y Evolución de Plantas, Instituto de EcologíaUniversidad Nacional Autónoma de MéxicoMéxico D.F.México
  3. 3.Centro de Ciencias de la Complejidad, piso 6, ala norte, Torre de IngenieríaUniversidad Nacional Autónoma de MéxicoMéxico D.F.México

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