Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees

被引:2
|
作者
Baste, Julien [1 ]
Paul, Christophe [1 ]
Sau, Ignasi [1 ]
Scornavacca, Celine [2 ]
机构
[1] Univ Montpellier, CNRS, LIRMM, Montpellier, France
[2] Univ Montpellier, CNRS, IRD, EPHE,Inst Sci Evolt, Montpellier, France
关键词
Phylogenetics; Compatibility; Unrooted phylogenetic trees; Parameterized complexity; FPT algorithm; Dynamic programming; ROOTED TREES; RECONSTRUCTION; COMPLEXITY;
D O I
10.1007/978-3-319-41168-2_5
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree - a tree having its leaves univocally labeled by elements of X and without degree-2 nodes - called the "species tree". One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g. DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the "concordance" with the input trees. The so-obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping - but not identical - sets of labels, is called "supertree". In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of "containing as a minor" and "containing as a topological minor" in the graph community. Both problems are known to be fixed-parameter tractable in the number of input trees k, by using their expressibility in Monadic Second Order Logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time 2(O(k2)). n, where n is the total size of the input.
引用
收藏
页码:53 / 64
页数:12
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