Inbunden, Engelska, 2010
Phylogenetic Networks
Concepts, Algorithms and Applications
Av Daniel H. Huson, Regula Rupp, Celine Scornavacca
1399 kr
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Beskrivning
Produktinformation
- Utgivningsdatum: 2010-12-02
- Mått: 179 x 253 x 20 mm
- Vikt: 890 g
- Format: Inbunden
- Språk: Engelska
- Antal sidor: 376
- Förlag: Cambridge University Press
- ISBN: 9780521755962
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Mer information
Daniel H. Huson is Professor of Algorithms in Bioinformatics at Tübingen 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 Tübingen 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 Tübingen University. She received her PhD in Computer Science from Montpellier University in 2009.
Recensioner i media
'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 Tübingen 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
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