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9781493938193

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This book is the result ... of a fruitful and long collaboration between a mathematician and a cell biologist. Capturing the best of both worlds, the book provides not only the biology and mathematical background for this topic, but also offers numerous examples which render it accessible to (post-graduate) students and researchers ... . this book can be treated as an excellent textbook for a wide audience varying from students to lecturers. (Irina Ioana Mohorianu, zbMATH 1312.92004, 2015) This book treats the theory of several important types of branching processes and demonstrates their usefulness by many interesting and important applications. ... Mathematical theory and biological applications are nicely interwoven. This text will be useful both to mathematicians (including graduate students) interested in relevant applications of stochastic processes in biology, as well as to mathematically oriented biologists working on the above mentioned topics. (R. Burger, Monatshefte fur Mathematik, Vol. 143 (1), 2004) This is a significant book on applications of branching processes in biology, and it is highly recommended for those readers who are interested in the application and development of stochastic models, particularly those with interests in cellular and molecular biology. (Charles J. Mode, Siam Review, Vol. 45 (2), 2003) This is a book written jointly by a mathematician and a cell biologist, who have collaborated on research in branching processes for more than a decade. In their own words, their monograph is intended for 'mathematicians and statisticians who have had an introduction to stochastic processes but have forgotten much of their college biology, and for biologists who wish to collaborate with mathematicians and statisticians.' They have largely succeeded in achieving their goal. The book can be strongly recommended to all students of branching processes; all libraries should have a copy. -ZENTRALBLATT MATH

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Marek Kimmel is a Professor of Statistics at Rice University. Professor Kimmel's research focuses on probabilistic modeling and statistical analysis in biosciences. He is particularly interested in applications of his work in cell and molecular biology and in cancer research. From the mathematical point of view, his interests lie in Markov and branching processes and in estimation theory. David Axelrod is a Professor at Rutgers University, where he works in a laboratory focusing on the heterogeneity and progression of human breast cancers using methods of molecular biology, cell biology, computer simulation, and mathematical modeling.

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