DocumentCode
110450
Title
Merging Partially Labelled Trees: Hardness and a Declarative Programming Solution
Author
Labarre, Anthony ; Verwer, Sicco
Author_Institution
Lab. d´Inf. Gaspard Monge, Univ. Paris-Est Marne-la-Vallee, Champs-sur-Marne, France
Volume
11
Issue
2
fYear
2014
fDate
March-April 2014
Firstpage
389
Lastpage
397
Abstract
Intraspecific studies often make use of haplotype networks instead of gene genealogies to represent the evolution of a set of genes. Cassens et al. proposed one such network reconstruction method, based on the global maximum parsimony principle, which was later recast by the first author of the present work as the problem of finding a minimum common supergraph of a set of t partially labelled trees. Although algorithms have been proposed for solving that problem on two graphs, the complexity of the general problem on trees remains unknown. In this paper, we show that the corresponding decision problem is NP-complete for t=3. We then propose a declarative programming approach to solving the problem to optimality in practice, as well as a heuristic approach, both based on the idpsystem, and assess the performance of both methods on randomly generated data.
Keywords
DNA; biology computing; decision making; evolution (biological); genetics; heuristic programming; molecular biophysics; trees (mathematics); IDP system; decision problem; declarative programming solution; gene genealogies; gene sets; global maximum parsimony principle; haplotype networks; hardness; merging partially labelled trees; minimum common supergraph; network reconstruction method; randomly generated data; Bioinformatics; Complexity theory; Computational biology; Labeling; Phylogeny; Vegetation; NP-hardness,satsolver, idp; Phylogenetic networks; supergraphs;
fLanguage
English
Journal_Title
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher
ieee
ISSN
1545-5963
Type
jour
DOI
10.1109/TCBB.2014.2307200
Filename
6746225
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