Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Efficient Reconstruction of Phylogenetic Networks with Constrained Recombination
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
Reconstructing reticulate evolution in species: theory and practice
RECOMB '04 Proceedings of the eighth annual international conference on Resaerch in computational molecular biology
Computing recombination networks from binary sequences
Bioinformatics
Computing the minimum number of hybridization events for a consistent evolutionary history
Discrete Applied Mathematics
Reducing distortion in phylogenetic networks
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Reconstruction of reticulate networks from gene trees
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
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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The result of a multiple gene tree analysis is usually a number of different tree topologies that are each supported by a significant proportion of the genes. We introduce the concept of a cluster network that can be used to combine such trees into a single rooted network, which can be drawn either as a cladogram or phylogram. In contrast to split networks, which can grow exponentially in the size of the input, cluster networks grow only quadratically. A cluster network is easily computed using a modification of the tree-popping algorithm, which we call network-popping. The approach has been implemented as part of the Dendroscope tree-drawing program and its application is illustrated using data and results from three recent studies on large numbers of gene trees.