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Introduction to Stochastic Processes with Applications to Biology

Linda J. S. Allen
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Ab Ilit
advanced stochastic biology applications
Author_Linda J. S. Allen
Biological Applications
birth and death process
branching process
Category=PBWL
Category=PS
Cellular Biology
Competition Model
CTMC
CTMC Model
drug kinetics
Embedded Markov Chain
epidemic analysis
Epidemic Model
epidemic process
epidemiology
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
Euler Maruyama Method
Expectation Matrix
Finite Markov Chain
Galton Watson Branching Process
Generating Function Technique
Kolmogorov Differential Equations
Markov Chain
Markov chains
Markov processes
mathematical modeling
MATLAB
Molecular Biology
Monte Carlo simulation
multivariate processes
Ordinary Differential Equation
population dynamics
population genetics
Positive Recurrent
predator-prey process
probability models
quantitative biology
Sample Paths
SDE Model
Simple Birth
Sir Epidemic
Sir Epidemic Model
Sis Epidemic Model
Stationary Probability Distribution
Stochastic Differential Equations
Stochastic Processes
stochastic simulation
Systems Biology
Transition Matrix
Wright Fisher Model

Product details

  • ISBN 9781439818824
  • Weight: 1080g
  • Dimensions: 156 x 234mm
  • Publication Date: 02 Dec 2010
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

An Introduction to Stochastic Processes with Applications to Biology, Second Edition presents the basic theory of stochastic processes necessary in understanding and applying stochastic methods to biological problems in areas such as population growth and extinction, drug kinetics, two-species competition and predation, the spread of epidemics, and the genetics of inbreeding. Because of their rich structure, the text focuses on discrete and continuous time Markov chains and continuous time and state Markov processes.

New to the Second Edition

  • A new chapter on stochastic differential equations that extends the basic theory to multivariate processes, including multivariate forward and backward Kolmogorov differential equations and the multivariate Itô’s formula
  • The inclusion of examples and exercises from cellular and molecular biology
  • Double the number of exercises and MATLAB® programs at the end of each chapter
  • Answers and hints to selected exercises in the appendix
  • Additional references from the literature

This edition continues to provide an excellent introduction to the fundamental theory of stochastic processes, along with a wide range of applications from the biological sciences. To better visualize the dynamics of stochastic processes, MATLAB programs are provided in the chapter appendices.

About Linda J. S. Allen

Linda J.S. Allen is a Paul Whitfield Horn Professor in the Department of Mathematics and Statistics at Texas Tech University. Dr. Allen has served on the editorial boards of the Journal of Biological Dynamics, SIAM Journal of Applied Mathematics, Journal of Difference Equations and Applications, Journal of Theoretical Biology, and Mathematical Biosciences. Her research interests encompass mathematical population biology, epidemiology, and immunology.

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