Biological evolution is the phenomenon concerning how species are born, are transformed or disappear over time. Its study relies on sophisticated methods that involve both mathematical modeling of the biological processes at play and the design of efficient algorithms to fit these models to genetic and morphological data.
Models and Methods for Biological Evolution outlines the main methods to study evolution and provides a broad overview illustrating the variety of formal approaches used, notably including combinatorial optimization, stochastic models and statistical inference techniques.
Some of the most relevant applications of these methods are detailed, concerning, for example, the study of migratory events of ancient human populations or the progression of epidemics.
This book should thus be of interest to applied mathematicians interested in central problems in biology, and to biologists eager to get a deeper understanding of widely used techniques of evolutionary data analysis.
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Gilles Didier is a researcher in applied mathematics at the Institut Montpellierain Alexander Grothendieck (IMAG), a joint research unit of the Université de Montpellier and the CNRS, France. He is particularly interested in the modeling of biological evolution.
Stéphane Guindon is a researcher at the Computer Science, Robotics and Microelectronics Laboratory of Montpellier (LIRMM), a joint research unit of the Université de Montpellier and the CNRS France. His studies focus on probabilistic models describing evolution at different time scales.
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Hardcover. Condition: new. Hardcover. Biological evolution is the phenomenon concerning how species are born, are transformed or disappear over time. Its study relies on sophisticated methods that involve both mathematical modeling of the biological processes at play and the design of efficient algorithms to fit these models to genetic and morphological data. Models and Methods for Biological Evolution outlines the main methods to study evolution and provides a broad overview illustrating the variety of formal approaches used, notably including combinatorial optimization, stochastic models and statistical inference techniques. Some of the most relevant applications of these methods are detailed, concerning, for example, the study of migratory events of ancient human populations or the progression of epidemics. This book should thus be of interest to applied mathematicians interested in central problems in biology, and to biologists eager to get a deeper understanding of widely used techniques of evolutionary data analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781789450699
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