Parameter estimation for Boolean models of biological networks

  • Authors:

  • Elena Dimitrova;Luis David García-Puente;Franziska Hinkelmann;Abdul S. Jarrah;Reinhard Laubenbacher;Brandilyn Stigler;Michael Stillman;Paola Vera-Licona

  • Affiliations:

  • Department of Mathematical Sciences, Clemson University, Clemson, SC 29634-0975, USA;Department of Mathematics and Statistics, Sam Houston State University, Huntsville, TX 77341-2206, USA and Statistical and Applied Mathematical Sciences Institute, Research Triangle Park, NC 27709 ...;Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0123, USA and Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State Unive ...;Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0123, USA and Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State Unive ...;Department of Mathematics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0123, USA and Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State Unive ...;Mathematics Department, Southern Methodist University, Dallas, TX 75275-0156, USA and Statistical and Applied Mathematical Sciences Institute, Research Triangle Park, NC 27709-4006, USA;Mathematics Department, Cornell University, Ithaca, NY 14853-4201, USA;Institut Curie Bioinformatics and Computational Systems Biology of Cancer, 26 rue dUlm, 75248 Paris, Cedex 05, France

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2011

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Abstract

Boolean networks have long been used as models of molecular networks, and they play an increasingly important role in systems biology. This paper describes a software package, Polynome, offered as a web service, that helps users construct Boolean network models based on experimental data and biological input. The key feature is a discrete analog of parameter estimation for continuous models. With only experimental data as input, the software can be used as a tool for reverse-engineering of Boolean network models from experimental time course data.