Integer linear programming as a tool for constructing trees from quartet data

Integer linear programming as a tool for constructing trees from quartet data

The task of the quartet puzzling problem is to find a best-fitting binary X-tree for a finite n-set from confidence values for the 3 n 4 binary trees with exactly four leaves from X, its fitness being measured by the sum of the confidence values of all “induced” four-leaves subtrees. We describe a m...

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Veröffentlicht in:Computational biology and chemistry 2005-06, Vol.29 (3), p.196-203
Hauptverfasser: Weyer-Menkhoff, Jan, Devauchelle, Claudine, Grossmann, Alex, Grünewald, Stefan
Format: Artikel
Sprache:eng
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Integer linear programming
Mammals’ mitochondrial evolution
Observed rate matrix
Phylogeny
Weighted quartet
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container_end_page 203
container_issue 3
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container_title Computational biology and chemistry
container_volume 29
creator Weyer-Menkhoff, Jan
Devauchelle, Claudine
Grossmann, Alex
Grünewald, Stefan
description The task of the quartet puzzling problem is to find a best-fitting binary X-tree for a finite n-set from confidence values for the 3 n 4 binary trees with exactly four leaves from X, its fitness being measured by the sum of the confidence values of all “induced” four-leaves subtrees. We describe a method for finding an exact solution of this problem by integer linear programming. Similar procedures can also be used for finding, e.g. best-fitting “circular” networks. A crucial problem in this context is, of course, how to obtain the input confidence values for the quartet trees. We propose to use inner products of rate-matrix diagonals calculated for pairs of taxa and present the trees resulting from applying our approach to two data sets of up to 36 mitochondrial sequences of mammals including an outgroup.
doi_str_mv 10.1016/j.compbiolchem.2005.04.001
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subjects Integer linear programming
Mammals’ mitochondrial evolution
Observed rate matrix
Phylogeny
Weighted quartet
title Integer linear programming as a tool for constructing trees from quartet data
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