A supertree method for rooted trees
Discrete Applied Mathematics
WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
A Short Proof that Phylogenetic Tree Reconstruction by Maximum Likelihood Is Hard
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Minimum-Flip Supertrees: Complexity and Algorithms
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
FlipCut supertrees: towards matrix representation accuracy in polynomial time
COCOON'11 Proceedings of the 17th annual international conference on Computing and combinatorics
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Supertree methods allow to reconstruct large phylogenetic trees by combining smaller trees with overlapping leaf sets, into one, more comprehensive supertree. The most commonly used supertree method, matrix representation with parsimony (MRP), produces accurate supertrees but is rather slow due to the underlying hard optimization problem. In this paper, we present an extensive simulation study comparing the performance of MRP and the polynomial supertree methods Min-Cut Supertree, Modified MinCut Supertree, Build-with-distances, PhySIC, and PhySIC IST. We consider both quality and resolution of the reconstructed supertrees. Our findings illustrate the trade-off between accuracy and running time in supertree construction, as well as the pros and cons of voting- and veto-based supertree approaches.