Chapter title |
Inferring Trees.
|
---|---|
Chapter number | 14 |
Book title |
Bioinformatics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6622-6_14 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6620-2, 978-1-4939-6622-6
|
Authors |
Simon Whelan, David A. Morrison |
Editors |
Jonathan M. Keith |
Abstract |
Molecular evolution can reveal the relationship between sets of homologous sequences and the patterns of change that occur during their evolution. An important aspect of these studies is the inference of a phylogenetic tree, which explicitly describes evolutionary relationships between homologous sequences. This chapter provides an introduction to evolutionary trees and how to infer them from sequence data using some commonly used inferential methodology. It focuses on statistical methods for inferring trees and how to assess the confidence one should have in any resulting tree, with a particular emphasis on the underlying assumptions of the methods and how they might affect the tree estimate. There is also some discussion of the underlying algorithms used to perform tree search and recommendations regarding the performance of different algorithms. Finally, there are a few practical guidelines, including how to combine multiple software packages to improve inference, and a comparison between Bayesian and Maximum likelihood phylogenetics. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 46 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 11 | 24% |
Researcher | 8 | 17% |
Student > Ph. D. Student | 7 | 15% |
Student > Master | 6 | 13% |
Student > Doctoral Student | 3 | 7% |
Other | 6 | 13% |
Unknown | 5 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 37% |
Biochemistry, Genetics and Molecular Biology | 16 | 35% |
Immunology and Microbiology | 2 | 4% |
Medicine and Dentistry | 2 | 4% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
Other | 1 | 2% |
Unknown | 7 | 15% |