
2010 / xiv + 267 pages / Softcover / ISBN: 9780898716924 / List Price $63.50 / SIAM Member Price $44.45 / Order Code OT118
Keywords: probabilistic boolean network, genetic network, computational biology, dynamical system, systems biology
Contents
Preface
Index
This is the first comprehensive treatment of probabilistic Boolean networks (PBNs), an important model class for studying genetic regulatory networks. This book covers basic model properties, including
It also discusses the inference of model parameters from experimental data and control strategies for driving network behavior towards desirable states.
The PBN model is well suited to serve as a mathematical framework to study basic issues dealing with systemsbased genomics, specifically, the relevant aspects of stochastic, nonlinear dynamical systems. The book builds a rigorous mathematical foundation for exploring these issues, which include
The authors attempt to unify different strands of current research and address emerging issues such as constrained control, greedy control, and asynchronicity.
Audience
Researchers in mathematics, computer science, and engineering are exposed to important applications in systems biology and presented with ample opportunities for developing new approaches and methods. The book is also appropriate for advanced undergraduates, graduate students, and scientists working in the fields of computational biology, genomic signal processing, control and systems theory, and computer science.
About the Authors
Ilya Shmulevich is a professor at the Institute for Systems Biology, Seattle, WA.
Edward R. Dougherty is a professor and director of the Genomic Signal Processing Laboratory at Texas A&M University, College Station, TX. He is also codirector of the Computational Biology Division of the Translational Genomics Research Institute, Phoenix, AZ.
ISBN: 9780898716924