Algorithmic research in phylogeny reconstruction. Tandy Warnow The University of Texas at Austin. Phylogeny. From the Tree of the Life Website, University of Arizona. Orangutan. Human. Gorilla. Chimpanzee. Reconstructing the “Tree” of Life. Handling large datasets: millions of species
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The University of Texas at Austin
From the Tree of the Life Website,University of Arizona
Handling large datasets: millions of species
NSF funds many projects
towards this goal, under
the Assembling the Tree of
Life (ATOL) program
Graph-theory, combinatorial optimization, probabilistic analysis, are fundamental to algorithm development in this area. But all methods are extensively tested in simulation and on real data as well. Collaborations with biologists or linguists are essential.
Phylogenetic treesApproaches for “solving” hard optimization problems (like maximum parsimony)
Shown here is the performance of a heuristic maximum parsimony analysis on a real dataset of almost 14,000 sequences. (“Optimal” here means best score to date, using any method for any amount of time.) Acceptable error is below 0.01%.
Performance of TNT with time
Simulation study based upon fixed edge lengths, K2P model of evolution, sequence lengths fixed to 1000 nucleotides.
Error rates reflect proportion of incorrect edges in inferred trees.
Base method M
Current best techniques
DCM boosted version of best techniques
Comparison of TNT to Rec-I-DCM3(TNT) on one large dataset
See http://www.phylo.org and http://www.cs.utexas.edu/~tandy for more info