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Books > Science & Mathematics > Biology, life sciences > Cellular biology
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Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology (Hardcover, 1st ed. 2017)
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Stochastic Processes, Multiscale Modeling, and Numerical Methods for Computational Cellular Biology (Hardcover, 1st ed. 2017)
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This book focuses on the modeling and mathematical analysis of
stochastic dynamical systems along with their simulations. The
collected chapters will review fundamental and current topics and
approaches to dynamical systems in cellular biology. This text aims
to develop improved mathematical and computational methods with
which to study biological processes. At the scale of a single cell,
stochasticity becomes important due to low copy numbers of
biological molecules, such as mRNA and proteins that take part in
biochemical reactions driving cellular processes. When trying to
describe such biological processes, the traditional deterministic
models are often inadequate, precisely because of these low copy
numbers. This book presents stochastic models, which are necessary
to account for small particle numbers and extrinsic noise sources.
The complexity of these models depend upon whether the biochemical
reactions are diffusion-limited or reaction-limited. In the former
case, one needs to adopt the framework of stochastic
reaction-diffusion models, while in the latter, one can describe
the processes by adopting the framework of Markov jump processes
and stochastic differential equations. Stochastic Processes,
Multiscale Modeling, and Numerical Methods for Computational
Cellular Biology will appeal to graduate students and researchers
in the fields of applied mathematics, biophysics, and cellular
biology.
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