This book develops the theory of continuous and discrete stochastic
processes within the context of cell biology. In the second edition
the material has been significantly expanded, particularly within
the context of nonequilibrium and self-organizing systems. Given
the amount of additional material, the book has been divided into
two volumes, with volume I mainly covering molecular processes and
volume II focusing on cellular processes. A wide range of
biological topics are covered in the new edition, including
stochastic ion channels and excitable systems, molecular motors,
stochastic gene networks, genetic switches and oscillators,
epigenetics, normal and anomalous diffusion in complex cellular
environments, stochastically-gated diffusion, active intracellular
transport, signal transduction, cell sensing, bacterial chemotaxis,
intracellular pattern formation, cell polarization, cell mechanics,
biological polymers and membranes, nuclear structure and dynamics,
biological condensates, molecular aggregation and nucleation,
cellular length control, cell mitosis, cell motility, cell
adhesion, cytoneme-based morphogenesis, bacterial growth, and
quorum sensing. The book also provides a pedagogical introduction
to the theory of stochastic and nonequilibrium processes - Fokker
Planck equations, stochastic differential equations, stochastic
calculus, master equations and jump Markov processes, birth-death
processes, Poisson processes, first passage time problems,
stochastic hybrid systems, queuing and renewal theory, narrow
capture and escape, extreme statistics, search processes and
stochastic resetting, exclusion processes, WKB methods, large
deviation theory, path integrals, martingales and branching
processes, numerical methods, linear response theory, phase
separation, fluctuation-dissipation theorems, age-structured
models, and statistical field theory. This text is primarily aimed
at graduate students and researchers working in mathematical
biology, statistical and biological physicists, and applied
mathematicians interested in stochastic modeling. Applied
probabilists should also find it of interest. It provides
significant background material in applied mathematics and
statistical physics, and introduces concepts in stochastic and
nonequilibrium processes via motivating biological applications.
The book is highly illustrated and contains a large number of
examples and exercises that further develop the models and ideas in
the body of the text. It is based on a course that the author has
taught at the University of Utah for many years.
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