Estimating Maximum Likelihood Phylogenies with PhyML
Centre National de la Recherche Scientifique · University of Auckland · +3 more institutions
Abstract
Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework. Moreover, phylogenetic inference provides sound statistical tools to exhibit the main features of molecular evolution from the analysis of actual sequences. This chapter focuses on phylogenetic tree estimation under the maximum likelihood (ML) principle. Phylogenies inferred under this probabilistic criterion are usually reliable and important biological hypotheses can be tested through the comparison of different models.…
Citation impact
- FWCI
- 57.69
- Percentile
- 100%
- References
- 50
Authors
4- SGStéphane GuindonCorresponding
Centre National de la Recherche Scientifique, University of Auckland
- FDFrédéric Delsuc
Université de Montpellier, Centre National de la Recherche Scientifique, Institut des Sciences de l'Evolution de Montpellier
- JDJean-François Dufayard
Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier, Centre National de la Recherche Scientifique
- OGOlivier Gascuel
Centre National de la Recherche Scientifique, Laboratoire d'Informatique, de Robotique et de Microélectronique de Montpellier
Topics & keywords
- Phylogenetic tree
- Inference
- Maximum likelihood
- Probabilistic logic
- Set (abstract data type)
- DECIPHER
- Biology
- Tree (set theory)