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Optimizing phylogenetic supertrees using answer set programming

Published online by Cambridge University Press:  03 September 2015

LAURA KOPONEN
Affiliation:
HIIT and Department of Computer Science, Aalto University, P.O. Box 15400, FI-00076 AALTO, Finland (e-mail: Laura.J.Koponen@aalto.fi, Emilia.Oikarinen@aalto.fi, Tomi.Janhunen@aalto.fi)
EMILIA OIKARINEN
Affiliation:
HIIT and Department of Computer Science, Aalto University, P.O. Box 15400, FI-00076 AALTO, Finland (e-mail: Laura.J.Koponen@aalto.fi, Emilia.Oikarinen@aalto.fi, Tomi.Janhunen@aalto.fi)
TOMI JANHUNEN
Affiliation:
HIIT and Department of Computer Science, Aalto University, P.O. Box 15400, FI-00076 AALTO, Finland (e-mail: Laura.J.Koponen@aalto.fi, Emilia.Oikarinen@aalto.fi, Tomi.Janhunen@aalto.fi)
LAURA SÄILÄ
Affiliation:
Department of Geosciences and Geography, University of HelsinkiP.O. Box 64, FI-00014 University of Helsinki, Finland (e-mail: Laura.Saila@helsinki.fi)

Abstract

The supertree construction problem is about combining several phylogenetic trees with possibly conflicting information into a single tree that has all the leaves of the source trees as its leaves and the relationships between the leaves are as consistent with the source trees as possible. This leads to an optimization problem that is computationally challenging and typically heuristic methods, such as matrix representation with parsimony (MRP), are used. In this paper we consider the use of answer set programming to solve the supertree construction problem in terms of two alternative encodings. The first is based on an existing encoding of trees using substructures known as quartets, while the other novel encoding captures the relationships present in trees through direct projections. We use these encodings to compute a genus-level supertree for the family of cats (Felidae). Furthermore, we compare our results to recent supertrees obtained by the MRP method.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2015 

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