Distance matrix methods
Statistical support for phylogenies
Does phylogenetic inference find correct trees?
Caveats with determining phylogenetic trees ...
How does cladistic analysis work, especially given the possibility of conflicting data generated by reversals and convergence?
NJplot is especially convenient for rooting the unrooted trees obtained from parsimony, distance or maximum likelihood tree-building methods.
Parsimony, Phylogeny, and Genomics. Oxford University Press, 3-55. ISBN 0199297304.
^ Aldous, David (1996), "Probability Distributions on Cladograms", Random Discrete Structures, Springer, p. 13
^ Lowe, Andrew (2004). Ecological Genetics: Design, Analysis, and Application.
This assumption, which we call strong parsimony, posits that due to expansion dynamics, there are a small number of subpopulations still present in the tumor ,, and that many of the VAF clusters are vestigial.
Almost always the "correct" cladogram employs the principle of parsimony, which proposes that the shortest number of steps or character state changes is most likely correct. An important question....is evolution always parsimonmious?
The principles of maximum parsimony and maximum likelihood help systematists reconstruct phylogeny.
As available data about DNA sequences increase, it becomes more difficult to draw the phylogenetic tree that best describes evolutionary history.
There are three main methods of constructing phylogenetic trees: Distance based methods such as Neighbour Joining, Parsimony based methods such as Maximum Parsimony , and character based methods such as Maximum Likelihood or Bayesian inference.
A parsimony tree gave essentially the same topology. Dots indicate the locations of inferred duplication events in the tree. Presumed pseudogenes are marked with ψ.
Phylogenetic trees are generally compared based on the principle of parsimony (Occam's razor.) ...
When equivalent possibilities turn up, one is usually chosen based on the principle of parsimony: the most compact arrangement is likely the best (a variation of Occam's razor).
genome evolution poses many exciting challenges to developers of mathematical models and algorithms, who have recourse to a spectra of algorithmic, statistical and mathematical techniques, ranging from exact, heuristics, fixed parameter and approximation algorithms for problems based on parsimony ...
See also: Biology, DNA, Evolution, Trans, Organ