Computational phylogenetics
Computational phylogenetics is the application of com-
putational algorithms, methods and programs to phylo-
genetic 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 ex-
ample, 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 organ-
isms.[2] Traditional phylogenetics relies on morphologic-
al 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 classifica-
tion. Many forms of molecular phylogenetics are closely
related to and make extensive use of sequence align-
ment 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 re-
produce the evolutionary tree that represents the his-
torical relationships between the species being analyzed.
The historical species tree may also differ from the his-
torical 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 se-
quences of interest. Progressive sequence alignment
methods produce a phylogenetic tree by necessity be-
cause they incorporate new sequences into the calcu-
lated alignment in order of g