
Leo van Iersel,
Steven Kelk and
Matthias Mnich. Uniqueness, intractability and exact algorithms: reflections on levelk phylogenetic networks. In JBCB, Vol. 7(4):597623, 2009. Keywords: explicit network, from triplets, galled tree, level k phylogenetic network, NP complete, phylogenetic network, phylogeny, reconstruction, uniqueness. Note: http://arxiv.org/pdf/0712.2932v2.



Ran LibeskindHadas and
Michael A. Charleston. On the Computational Complexity of the Reticulate Cophylogeny Reconstruction Problem. In JCB, Vol. 16(1):105117, 2009. Keywords: cophylogeny, heuristic, NP complete, parsimony, phylogenetic network, reconstruction. Note: http://dx.doi.org/10.1089/cmb.2008.0084.
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"The cophylogeny reconstruction problem is that of finding minimal cost explanations of differences between evolutionary histories of ecologically linked groups of biological organisms. We present a proof that shows that the general problem of reconciling evolutionary histories is NPcomplete and provide a sharp boundary where this intractability begins. We also show that a related problem, that of finding Pareto optimal solutions, is NPhard. As a byproduct of our results, we give a framework by which metaheuristics can be applied to find good solutions to this problem. © Mary Ann Liebert, Inc. 2009."



Daniel H. Huson,
Regula Rupp,
Vincent Berry,
Philippe Gambette and
Christophe Paul. Computing Galled Networks from Real Data. In ISMBECCB09, Vol. 25(12):i85i93 of BIO, 2009. Keywords: abstract network, cluster containment, explicit network, FPT, from clusters, from rooted trees, galled network, NP complete, phylogenetic network, phylogeny, polynomial, Program Dendroscope, reconstruction. Note: http://hallirmm.ccsd.cnrs.fr/lirmm00368545/en/.
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"Motivation: Developing methods for computing phylogenetic networks from biological data is an important problem posed by molecular evolution and much work is currently being undertaken in this area. Although promising approaches exist, there are no tools available that biologists could easily and routinely use to compute rooted phylogenetic networks on real datasets containing tens or hundreds of taxa. Biologists are interested in clades, i.e. groups of monophyletic taxa, and these are usually represented by clusters in a rooted phylogenetic tree. The problem of computing an optimal rooted phylogenetic network from a set of clusters, is hard, in general. Indeed, even the problem of just determining whether a given network contains a given cluster is hard. Hence, some researchers have focused on topologically restricted classes of networks, such as galled trees and levelk networks, that are more tractable, but have the practical drawback that a given set of clusters will usually not possess such a representation. Results: In this article, we argue that galled networks (a generalization of galled trees) provide a good tradeoff between level of generality and tractability. Any set of clusters can be represented by some galled network and the question whether a cluster is contained in such a network is easy to solve. Although the computation of an optimal galled network involves successively solving instances of two different NPcomplete problems, in practice our algorithm solves this problem exactly on large datasets containing hundreds of taxa and many reticulations in seconds, as illustrated by a dataset containing 279 prokaryotes. © 2009 The Author(s)."



Ali Tofigh. Using Trees to Capture Reticulate Evolution, Lateral Gene Transfers and Cancer Progression. PhD thesis, KTH Royal Institute of Technology, Sweden, 2009. Keywords: duplication, dynamic programming, from multilabeled tree, from rooted trees, from species tree, lateral gene transfer, loss, NP complete, phylogenetic network, phylogeny, reconstruction. Note: http://kth.divaportal.org/smash/record.jsf?pid=diva2:220830&searchId=1.


