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.
1. Trees: Combinatorics and Models, Gilles Didier and Stéphane Guindon.
2. Models of Sequences and Discrete Traits Evolution, Étienne Pardoux.
3. Evolutionary Models of Continuous Traits, Paul Bastide, Mahendra Mariadassou, and Stéphane Robin.
4. Correlated Evolution: Models and Methods, Guillaume Achaz and Julien Y. Dutheil.
5. A Century of Genomic Rearrangements, Anne Bergeron and Krister M. Swenson.
6. Phylogenetic Inference: Distance-Based Methods, Fabio Pardi.
7. Computing Inference in Phylogenetic Trees, Laurent Guéguen.
8. The Bayesian Paradigm in Molecular Phylogeny, Nicolas Rodrigue.
9. Measures of Branch Support in Phylogenetics, Olivier Gascuel and Frédéric Lemoine.
10. Fossils and Phylogeny, Michel Laurin.
11. Phylodynamics, Samuel Alizon.
12. Inference of Demographic Processes in Human Populations, Frédéric Austerlitz.
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.
Table of Contents
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