Cadran's summer at Texas A&M with the the Distributed Mentor Program (DMP)

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Abstract


Phylogenetic studies often produce thousands of trees that each represents a possible evolutionary history for a set of taxa. Large numbers of trees are difficult to analyze, particularly because there are few existing methods to do so. One common technique is to compute a representative strict consensus tree, but this approach can cause information about individual trees to be lost when their topologies are notably different. This paper investigates clustering as a tool to evaluate trees collected during the heuristic search process and employs the Cluster Grid and Tessellation Plot as tools to graphically interpret them. We identify some topological features of the trees within search spaces and present the cluster grid and tessellation plot as useful methods for visualizing relationships among them. [full text]



© Cadran Cowansage, 2007