DocumentCode :
1340730
Title :
On the Elusiveness of Clusters
Author :
Kelk, S. ; Scornavacca, C. ; van Iersel, L.
Author_Institution :
Dept. of Knowledge Eng. (DKE), Maastricht Univ., Maastricht, Netherlands
Volume :
9
Issue :
2
fYear :
2012
Firstpage :
517
Lastpage :
534
Abstract :
Rooted phylogenetic networks are often used to represent conflicting phylogenetic signals. Given a set of clusters, a network is said to represent these clusters in the softwiredsense if, for each cluster in the input set, at least one tree embedded in the network contains that cluster. Motivated by parsimony we might wish to construct such a network using as few reticulations as possible, or minimizing the level of the network, i.e., the maximum number of reticulations used in any "tangled" region of the network. Although these are NP-hard problems, here we prove that, for every fixed k ≥ 0, it is polynomial-time solvable to construct a phylogenetic network with level equal to k representing a cluster set, or to determine that no such network exists. However, this algorithm does not lend itself to a practical implementation. We also prove that the comparatively efficient CASS algorithm correctly solves this problem (and also minimizes the reticulation number) when input clusters are obtained from two not necessarily binary gene trees on the same set of taxa but does not always minimize level for general cluster sets. Finally, we describe a new algorithm which generates in polynomial-time all binary phylogenetic networks with exactly r reticulations representing a set of input clusters (for every fixed r ≥ 0).
Keywords :
biology computing; computational complexity; embedded systems; evolution (biological); genetics; optimisation; CASS algorithm; NP-hard problems; binary gene trees; cluster elusiveness; conflicting phylogenetic signals; least one tree embedded networks; parsimony motivation; polynomial-time solvable networks; reticulation number; rooted phylogenetic networks; softwired sense; tangled region; Binary trees; Clustering algorithms; Generators; Minimization; Phylogeny; Polynomials; Vegetation; Rooted phylogenetic networks; clusters; computational complexity; parsimony; polynomial-time algorithms.; reticulate evolution; Algorithms; Cluster Analysis; Computational Biology; Evolution, Molecular; Models, Genetic; Phylogeny;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2011.128
Filename :
6035670
Link To Document :
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