Numerical methods for inferring evolutionary trees
Despite a century of evolutionary theory, only in the last few decades have clearly defined procedures for inferring phylogenies been stated. For discrete characters whose ancestral states are known, the prescriptions of Hennig are well defined, but they are applicable only when there is no incompatibility between different characters. This limitation has led to the elaboration of a number of methods for dealing with such incompatibilities. Each method has a different set of implicit assumptions concerning the biology of the characters and the information available from the data. If the methods are considered in a statistical framework as different estimators of an unknown quantity (the phylogeny), these assumptions are more clearly seen. Standard statistical approaches, such as maximum likelihood, can be used to obtain methods whose properties are known and for which one can determine the amount of uncertainty in the resulting estimates of the phylogeny. Although existing statistical models are highly oversimplified and do not reflect the complexity of evolutionary processes, it is by viewing the problem as a statistical one that we can place all these methods in a common framework, within which their behavior and assumptions can be compared. 160 references, 3 figures.
- Research Organization:
- Univ. of Washington, Seattle
- DOE Contract Number:
- AT06-70EV71005; AM06-70RL02225
- OSTI ID:
- 5779372
- Journal Information:
- Q. Rev. Biol.; (United States), Journal Name: Q. Rev. Biol.; (United States) Vol. 57:4; ISSN QRBIA
- Country of Publication:
- United States
- Language:
- English
Similar Records
Confidence limits on phylogenies: an approach using the bootstrap
Inferring evolutionary trees from ordinal data