362 pages, Figs
The evolutionary history of species is traditionally represented using a rooted phylogenetic tree. However, when reticulate events such as hybridization, horizontal gene transfer or recombination are believed to be involved, phylogenetic networks that can accommodate non-treelike evolution have an important role to play. This book provides the first interdisciplinary overview of phylogenetic networks. Beginning with a concise introduction to both phylogenetic trees and phylogenetic networks, the fundamental concepts and results are then presented for both rooted and unrooted phylogenetic networks.
Current approaches and algorithms available for computing phylogenetic networks from different types of datasets are then discussed, accompanied by examples of their application to real biological datasets. The book also summarises the algorithms used for drawing phylogenetic networks, along with the existing software for their computation and evaluation. All datasets, examples and other additional information and links are available from the book's companion website at www.phylogenetic-networks.org.
Advance praise: 'Networks - rather than just trees - are fast becoming the essential tool for making sense of the complexities of evolution, and conflicting signal[s] in genomic data. Phylogenetic Networks provides a long-overdue exposition of network-based methods, their possible uses, and details on practical software. A detailed and unified treatment of the many different types of networks is complemented by a crisp synopsis of the underlying theory. Numerous example[s] and illustrations make the text easy to follow. This book will further transform the way biologists use genomic data to study evolution. The Tubingen group has led the development of phylogenetic network algorithms, and this book delivers a clear exposition for biologists bewildered by a plethora of recent methods, as well as for bioinformaticians aiming to develop the field further. It is essential reading for any scientist or student seeking to understand how genomic data can be used to represent and study the intricate 'web of life'.' Mike Steel, University of Canterbury 'This textbook, by one of the leaders of the field (Daniel Huson) and his co-authors, provides a mathematically rigorous introduction to one of the most exciting and beautiful research areas in computational biology: phylogenetic networks. The text is clear and provides all the necessary biology background; it should be accessible to graduate students (or upper-division undergraduates) in mathematics, computer science, or statistics.' Tandy Warnow, University of Texas 'This wonderfully accessible book is by far the most thorough and up-to-date treatment of phylogenetic networks about. Many evolutionary processes in nature do not conform to the simple model of phylogenetic trees; examples are hybridizations, symbioses, and lateral gene transfer. The more we probe nature with genomics, the more significant and numerous these examples become, so there is a real need for using networks in phylogenetics. This volume is a must for researchers working with phylogenetic networks. It is for an advanced college audience. Beautifully organized and clearly written, it really fills a void.' Bill Martin, University of Dusseldorf
Part I. Introduction: 1. Basics; 2. Sequence alignment; 3. Phylogenetic trees; 4. Phylogenetic networks; Part II. Theory: 5. Clusters and rooted phylogenetic networks; 6. Splits and unrooted phylogenetic networks; Part III. Algorithms and Applications: 7. Phylogenetic networks from clusters; 8. Phylogenetic networks from splits; 9. Phylogenetic networks from sequences; 10. Phylogenetic networks from distances; 11. Phylogenetic networks from trees; 12. Phylogenetic networks from triplets or quartets; 13. Drawing phylogenetic networks; 14. Software; Glossary; Index.
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Daniel H. Huson is Professor of Algorithms in Bioinformatics at Tubingen University. He has authored numerous papers in bioinformatics, biology and mathematics, and is the main author of the widely-used computer programs Dendroscope, MEGAN and SplitsTree. Regula Rupp received her PhD in Mathematics from Bern University in 2006. Between 2007 and 2009 she held a postdoctoral research position at Tubingen University, working with Daniel H. Huson in developing robust methods for computing phylogenetic networks from real biological data. Celine Scornavacca is a postdoctoral researcher working on algorithms for phylogenetic networks with Daniel H. Huson at Tubingen University. She received her PhD in Computer Science from Montpellier University in 2009.