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Algorithms in Bioinformatics

Volume 6293 of the series Lecture Notes in Computer Science pp 288-299

An Experimental Study of Quartets MaxCut and Other Supertree Methods

  • M. Shel SwensonAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, The University of Texas at AustinDepartment of Mathematics, The University of Texas at Austin
  • , Rahul SuriAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, The University of Texas at Austin
  • , C. Randal LinderAffiliated withCarnegie Mellon UniversitySection of Integrative Biology, The University of Texas at Austin
  • , Tandy WarnowAffiliated withCarnegie Mellon UniversityDepartment of Computer Science, The University of Texas at Austin

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Abstract

Although many supertree methods have been developed in the last few decades, none has been shown to produce more accurate trees than the popular Matrix Representation with Parsimony (MRP) method. In this paper, we evaluate the performance of several supertree methods based upon the Quartets MaxCut method of Snir and Rao. We show that two of these methods usually outperform MRP and all other supertree methods we studied under many realistic model conditions. In addition, we show that the popular criterion of minimizing the total topological distance to the source trees is only weakly correlated with topological accuracy, and therefore that evaluating supertree methods on biological datasets is problematic.