TNT, a free program for phylogenetic analysis
Through the use of a number of native commands and a simple but powerful scripting language, TNT allows the user an enormous flexibility in phylogenetic analyses or simulations.
TNT version 1.5, including a full implementation of phylogenetic morphometrics
Using algorithms described in this paper, searches for landmark data can be made tens to hundreds of times faster than it was possible before, thus making phylogenetic analysis of landmarks feasible even on standard personal computers.
ESTIMATING CHARACTER WEIGHTS DURING TREE SEARCH
- P. Goloboff
- Computer ScienceCladistics
- 1 March 1993
Abstract— A new method for weighting characters according to their homoplasy is proposed; the method is non‐iterative and does not require independent estimations of weights. It is based on searching…
Analyzing Large Data Sets in Reasonable Times: Solutions for Composite Optima
- P. Goloboff
- 1 December 1999
New methods for parsimony analysis of large data sets are presented, including sectorial searches, tree‐drifting, and tree‐fusing which find a shortest tree in less than 10 min and perform well in other cases analyzed.
Improvements to resampling measures of group support
- P. Goloboff, J. Farris, M. Källersjö, B. Oxelman, Martıacute;n J Ramıacute;rez, C. Szumik
- 1 August 2003
Several aspects of current resampling methods to assess group support are reviewed. When the characters have different prior weights or some state transformation costs are different, the frequencies…
Weighting against homoplasy improves phylogenetic analysis of morphological data sets
The problem of character weighting in cladistic analysis is revisited. The finding that, in large molecular data sets, removal of third positions (with more homoplasy) decreases the number of well…
Continuous characters analyzed as such
Results suggest that continuous characters carry indeed phylogenetic information, and that (if they have been observed) there is no real reason to exclude them from the analysis.
An optimality criterion to determine areas of endemism.
This is the first method for the identification of areas of Endemism that implements an optimality criterion directly based on considering the aspects of species distribution that are relevant to endemism.
Areas of endemism: an improved optimality criterion.
Algorithms to evaluate areas of endemism under this criterion are discussed, and implemented in a computer program (NDM), which allow evaluation of much larger data sets.
Methods for Quick Consensus Estimation
A way to collapse branches considering suboptimal trees is described, which can be extended as a measure of relative support for groups; the relative support is based on the Bremer support, but takes into account relative amounts of favorable and contradictory evidence.