Probabilistic Boolean Networks
The Modeling and Control of Gene Regulatory Networks
Published on 21. January 2010
Book
Paperback/Softback
184 pages
978-0-89871-692-4 (ISBN)
Description
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 the relationships between network structure and dynamics, steady-state analysis, and relationships to other model classes. 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 systems-based genomics, specifically, the relevant aspects of stochastic, nonlinear dynamical systems. The book builds a rigorous mathematical foundation for exploring these issues, which include long-run dynamical properties and how these correspond to therapeutic goals; the effect of complexity on model inference and the resulting consequences of model uncertainty; altering network dynamics via structural intervention, such as perturbing gene logic; optimal control of regulatory networks over time; limitations imposed on the ability to achieve optimal control owing to model complexity; and the effects of asynchronicity.
The authors attempt to unify different strands of current research and address emerging issues such as constrained control, greedy control, and asynchronicity.
The PBN model is well suited to serve as a mathematical framework to study basic issues dealing with systems-based genomics, specifically, the relevant aspects of stochastic, nonlinear dynamical systems. The book builds a rigorous mathematical foundation for exploring these issues, which include long-run dynamical properties and how these correspond to therapeutic goals; the effect of complexity on model inference and the resulting consequences of model uncertainty; altering network dynamics via structural intervention, such as perturbing gene logic; optimal control of regulatory networks over time; limitations imposed on the ability to achieve optimal control owing to model complexity; and the effects of asynchronicity.
The authors attempt to unify different strands of current research and address emerging issues such as constrained control, greedy control, and asynchronicity.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
College/higher education
Professional and scholarly
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.
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 257 mm
Width: 182 mm
Thickness: 22 mm
Weight
544 gr
ISBN-13
978-0-89871-692-4 (9780898716924)
Schweitzer Classification
Persons
Ilya Shmulevich is a Professor at the Institute for Systems Biology, Seattle, WA. Dr Shmulevich received his Ph.D. degree in Electrical and Computer Engineering from Purdue University, West Lafayette, IN, USA, in 1997. He has since worked at the University of Nijmegen, the University of Amsterdam, Tampere University of Technology, the University of Texas and Rice University.
Content
Preface; 1. Boolean networks; 2. Structure and dynamics of probabilistic Boolean networks; 3. Inference of model structure; 4. Structural intervention; 5. External control; 6. Asynchronous networks; Bibliography; Index.