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FlipCut supertrees: Computing larger, better phylogenies faster

Fachliche Zuordnung Bioinformatik und Theoretische Biologie
Förderung Förderung von 2012 bis 2016
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 211926079
 
Supertree approaches combine input trees with overlapping taxa sets into one large and more comprehensive tree. Here, the problem is dealing with incompatible data in a reasonable way. Supertree methods can be used as part of a divide-and-conquer approach for phylogenetic tree inference: (1) we compute, say, maximum likelihood (ML) trees for several subsets of taxa; (2) we merge the resulting trees into one supertree; (3) finally, we use this supertree as a seed for an ML analysis on the complete set of taxa. Current supertree methods suffer from being too slow or too inaccurate when analyzing large datasets. We have recently developed a novel supertree called FLIPCUT supertrees, which is very swift and computes supertrees of good quality. In this project, we will further advance this methods so that supertree quality is on a par with the current supertree “gold standard” Matrix Representation with Parsimony (MRP). At the same time, we want to preserve the extraordinary swiftness of the method. We will then integrate the resulting method into a divide-and-conquer approach for phylogenetic reconstruction, and evaluate it against “pure” ML programs.
DFG-Verfahren Sachbeihilfen
 
 

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