Stability analysis of phylogenetic trees
Author(s) -
Saad I. Sheikh,
Tamer Kahveci,
Sanjay Ranka,
J. Gordon Burleigh
Publication year - 2012
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bts657
Subject(s) - phylogenetic tree , tree (set theory) , phylogenetics , taxon , heuristic , stability (learning theory) , computer science , granularity , phylogenetic network , data mining , biology , machine learning , mathematics , artificial intelligence , ecology , combinatorics , biochemistry , gene , operating system
Phylogenetics, or reconstructing the evolutionary relationships of organisms, is critical for understanding evolution. A large number of heuristic algorithms for phylogenetics have been developed, some of which enable estimates of trees with tens of thousands of taxa. Such trees may not be robust, as small changes in the input data can cause major differences in the optimal topology. Tools that can assess the quality and stability of phylogenetic tree estimates and identify the most reliable parts of the tree are needed.
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