Computational phylogenetics is the application of computational algorithms, methods and programs to phylogenetic analyses. The goal is to assemble a phylogenetic tree representing a hypothesis about the evolutionary ancestry of a set of genes, species, or other taxa. For example, these techniques have been used to explore the family tree of hominid species[1] and the relationships between specific genes shared by many types of organisms.[2] Traditional phylogenetics relies on morphological data obtained by measuring and quantifying the phenotypic properties of representative organisms, while the more recent field of molecular phylogenetics uses nucleotide sequences encoding genes or amino acid sequences encoding proteins as the basis for classification. Many forms of molecular phylogenetics are closely related to and make extensive use of sequence alignment in constructing and refining phylogenetic trees, which are used to classify the evolutionary relationships between homologous genes represented in the genomes of divergent species. The phylogenetic trees constructed by computational methods are unlikely to perfectly reproduce the evolutionary tree that represents the historical relationships between the species being analyzed. The historical species tree may also differ from the historical tree of an individual homologous gene shared by those species.
Producing a phylogenetic tree requires a measure of homology among the characteristics shared by the taxa being compared. In morphological studies, this requires explicit decisions about which physical characteristics to measure and how to use them to encode distinct states corresponding to the input taxa. In molecular studies, a primary problem is in producing a multiple sequence alignment (MSA) between the genes or amino acid sequences of interest. Progressive sequence alignment methods produce a phylogenetic tree by necessity because they incorporate new sequences into the calculated alignment in order of genetic distance. Although a phylogenetic tree can always be constructed from an MSA, phylogenetics methods such as maximum parsimony and maximum likelihood do not require the production of an initial or concurrent MSA.
See also[]
- List of phylogenetics software
- Cladistics
- PHYLIP
- Phylogenetic comparative methods
- Phylogenetic tree
- Phylogenetics
- Systematics
- Joe Felsenstein
External links[]
- PHYLIP, a freely distributed phylogenetic analysis package
- PAUP, a similar analysis package available for purchase
- MrBayes, a program for the Bayesian estimation of phylogeny (software wiki)
- BAli-Phy, a program for simultaneous Bayesian estimation of alignment and phylogeny.
- Treefinder, a graphical analysis environment for molecular phylogenetics
- Modeltest, a program for selecting appropriate substitution models for nucleotide sequences
- CIPRES: Cyberinfrastructure for Phylogenetic Research
- Phylogenetic inferring on the T-REX server
- List of phylogeny programs
- Phylogeny Algorithms Pseudocode
References[]
Further reading[]
- Charles Semple (2003), Phylogenetics, Oxford University Press, ISBN 9780198509424
- Barry A. Cipra (2007), Algebraic Geometers See Ideal Approach to Biology, SIAM News, Volume 40, Number 6
| Phylogenetics |
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Basic concepts — Synapomorphy • Phylogenetic tree • Phylogenetic network • Long branch attraction • Clade Inference methods — Maximum parsimony • Maximum likelihood • Neighbor-joining • UPGMA • Bayesian inference • Least squares Current topics — PhyloCode • DNA barcoding -morphy — Symplesiomorphy • Apomorphy • Plesiomorphy • Synapomorphy -phyly — Monophyly/Holophyly • Paraphyly • Polyphyly |
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