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Probabilistic Boolean Networks - The Modeling and Control of Gene Regulatory Networks (Paperback, New)
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Probabilistic Boolean Networks - The Modeling and Control of Gene Regulatory Networks (Paperback, New)
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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.
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