ITR: Evaluating Phylogeny Reconstruction Algorithms with Digital Organisms

Michigan State University, East Lansing MI

Investigators

Abstract

EIA-0219229 Torng, Eric K Michigan State University ITR: Evaluating Phylogeny Reconstruction Algorithms with Digital Organisms The investigators study methods of determining the historic relationship between species using only knowledge of currently existing organisms, a technique called "phylogenetic tree reconstruction". Many tree reconstruction algorithms are known, but it is difficult to properly test them for the very reason that the algorithms are useful -- the original trees are lost to history. The studies proposed make use of a new evaluation methodology based on an artificial evolving system called Avida. In Avida, populations of digital organisms (self-replicating computer programs) experience natural selection as they compete for limited resources, and will evolve into new species often with entirely new genes. The history of such a system can be monitored, and hence a reconstruction from the final state can have its accuracy measured. The proposed activity has several broader impacts on society. It is a core activity in the Center for Biological Modeling, a new interdisciplinary research and education center at Michigan State University. Undergraduate students including underrepresented minorities will be involved by studying small, self-contained questions. Finally, enhanced understanding of phylogeny reconstruction algorithms will improve our ability to interpret the sequences of genes, aiding in drug design and helping efforts to reconstruct an evolutionary "tree of life".