Computational Phylogenetics
An Introduction to Designing Methods for Phylogeny Estimation

This book presents the foundations of phylogeny estimation and technical material enabling researchers to develop improved computational methods.

Tandy Warnow (Author)

9781107184718, Cambridge University Press

Hardback, published 2 November 2017

394 pages, 58 b/w illus. 8 colour illus. 11 tables 250 exercises
25.3 x 17.7 x 2.2 cm, 0.94 kg

A comprehensive account of both basic and advanced material in phylogeny estimation, focusing on computational and statistical issues. No background in biology or computer science is assumed, and there is minimal use of mathematical formulas, meaning that students from many disciplines, including biology, computer science, statistics, and applied mathematics, will find the text accessible. The mathematical and statistical foundations of phylogeny estimation are presented rigorously, following which more advanced material is covered. This includes substantial chapters on multi-locus phylogeny estimation, supertree methods, multiple sequence alignment techniques, and designing methods for large-scale phylogeny estimation. The author provides key analytical techniques to prove theoretical properties about methods, as well as addressing performance in practice for methods for estimating trees. Research problems requiring novel computational methods are also presented, so that graduate students and researchers from varying disciplines will be able to enter the broad and exciting field of computational phylogenetics.

Preface
Glossary
Notation
Part I. Basic Techniques: 1. Brief introduction to phylogenetic estimation
2. Trees
3. Constructing trees from true subtrees
4. Constructing trees from qualitative characters
5. Distance-based tree estimation methods
6. Consensus and agreement trees
7. Supertrees
Part II. Molecular Phylogenetics: 8. Statistical gene tree estimation methods
9. Multiple sequence alignment
10. Phylogenomics: constructing species phylogenies from multi-locus data
11. Designing methods for large-scale phylogeny estimation
Appendix A. Primer on biological data and evolution
Appendix B. Algorithm design and analysis
Appendix C. Guidelines for writing papers about computational methods
Appendix D. Projects
References
Index.

Subject Areas: Algorithms & data structures [UMB], Biology, life sciences [PS], Probability & statistics [PBT], Discrete mathematics [PBD], Computational linguistics [CFX]