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Decoding Genomes demonstrates how to uncover information about past evolutionary and population dynamic processes based on genomic samples. The last decades have seen considerable theoretical and methodological advances in this area. These enable the assessment of critical scientific questions such as the impact of environmental changes on biodiversity and the evolution of pathogens during recent epidemics. The book gives the reader a detailed understanding of the whole process: from genome sampling to obtaining biological insights by applying sophisticated statistical and computational analyses. In particular, sequencing of genomic samples, the alignment of sequences, molecular evolution models, phylogenetics, and phylodynamics are core topics. Statistical and computational approaches discussed include dynamic programming, maximum likelihood, Bayesian statistics, and model selection, to name a few. The concepts introduced and applied throughout the book enable readers to answer questions across biological scales, including microevolution, macroevolution, immunology, development, cancer, and epidemiology, as well as in fields other than biology where evolutionary concepts are key, such as linguistics.
The book is for students and researchers who aim to analyse genomic sequence data or develop statistical and computational approaches for such analyses. The content is tailored to readers from a wide variety of backgrounds, ranging from mathematics and statistics, computer science, or physics to biology, and, more generally, the life sciences.
All authors are or have been part of the Computational Evolution group at ETH Zürich, which is widely recognised as one of the leading teams in developing evolutionary and population dynamic models for analysing genomic data. Their various backgrounds — including mathematics, computer science, physics, and biology — help make this work accessible to a broad audience.
This book is published under the CC BY-SA 4.0 license. All material included in the book falls under this license, with the sole exception of some figures which have been adapted from external sources. The license information for each of these figures is given in the figure list on page 359.
Chapter 9 contains several long mathematical derivations. Relevant algebraic transformations are contained in this Mathematica notebook file.
While every effort has been made to ensure the text of this book is free of errors, all products of biology are subject to mutations — including books. In the event that you identify errors in the text, we would be grateful if you could notify us by sending details of the error to errata@decodinggenomes.org.
We would also be happy to receive any other feedback at feedback@decodinggenomes.org.
All authors were employed by ETH Zürich while writing major parts of the book, and we gratefully acknowledge this support. Any profits made through selling the book in print will be used for our future educational projects.
Happy reading!