On the complexity of comparing evolutionary trees
Discrete Applied Mathematics - Special volume on computational molecular biology
Journal of Computer and System Sciences - Special issue on bioinformatics II
Computing the minimum number of hybridization events for a consistent evolutionary history
Discrete Applied Mathematics
Computing galled networks from real data
Bioinformatics
Beyond galled trees: decomposition and computation of galled networks
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
Constructing level-2 phylogenetic networks from triplets
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
A unifying view on approximation and FPT of agreement forests
WABI'09 Proceedings of the 9th international conference on Algorithms in bioinformatics
Phylogenetic Networks: Concepts, Algorithms and Applications
Phylogenetic Networks: Concepts, Algorithms and Applications
Algorithms for Reticulate Networks of Multiple Phylogenetic Trees
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Fast computation of minimum hybridization networks
Bioinformatics
Fast computation of the exact hybridization number of two phylogenetic trees
ISBRA'10 Proceedings of the 6th international conference on Bioinformatics Research and Applications
MURPAR: a fast heuristic for inferring parsimonious phylogenetic networks from multiple gene trees
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
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Phylogenetic network is a model for reticulate evolution. Hybridization network is one type of phylogenetic network for a set of discordant gene trees, and "displays" each gene tree. A central computational problem on hybridization networks is: given a set of gene trees, reconstruct the minimum (i.e. most parsimonious) hybridization network that displays each given gene tree. This problem is known to be NP-hard, and existing approaches for this problem are either heuristics or make simplifying assumptions (e.g. work with only two input trees or assume some topological properties). In this paper, we develop an exact algorithm (called PIRNC) for inferring the minimum hybridization networks from multiple gene trees. The PIRNC algorithm does not rely on structural assumptions. To the best of our knowledge, PIRNC is the first exact algorithm for this formulation. When the number of reticulation events is relatively small (say four or fewer), PIRNC runs reasonably efficient even for moderately large datasets. For building more complex networks, we also develop a heuristic version of PIRNC called PIRNCH. Simulation shows that PIRNCH usually produces networks with fewer reticulation events than those by an existing method.