| An ILP solution for the gene duplication problem. | |
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MedLine Citation:
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PMID: 21342543 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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BACKGROUND: The gene duplication (GD) problem seeks a species tree that implies the fewest gene duplication events across a given collection of gene trees. Solving this problem makes it possible to use large gene families with complex histories of duplication and loss to infer phylogenetic trees. However, the GD problem is NP-hard, and therefore, most analyses use heuristics that lack any performance guarantee. RESULTS: We describe the first integer linear programming (ILP) formulation to solve instances of the gene duplication problem exactly. With simulations, we demonstrate that the ILP solution can solve problem instances with up to 14 taxa. Furthermore, we apply the new ILP solution to solve the gene duplication problem for the seed plant phylogeny using a 12-taxon, 6,084-gene data set. The unique, optimal solution, which places Gnetales sister to the conifers, represents a new, large-scale genomic perspective on one of the most puzzling questions in plant systematics. CONCLUSIONS: Although the GD problem is NP-hard, our novel ILP solution for it can solve instances with data sets consisting of as many as 14 taxa and 1,000 genes in a few hours. These are the largest instances that have been solved to optimally to date. Thus, this work can provide large-scale genomic perspectives on phylogenetic questions that previously could only be addressed by heuristic estimates. |
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Authors:
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Wen-Chieh Chang; Gordon J Burleigh; David F Fernández-Baca; Oliver Eulenstein |
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Publication Detail:
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Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S. Date: 2011-02-15 |
Journal Detail:
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Title: BMC bioinformatics Volume: 12 Suppl 1 ISSN: 1471-2105 ISO Abbreviation: BMC Bioinformatics Publication Date: 2011 |
Date Detail:
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Created Date: 2011-02-23 Completed Date: 2011-04-08 Revised Date: 2011-07-26 |
Medline Journal Info:
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Nlm Unique ID: 100965194 Medline TA: BMC Bioinformatics Country: England |
Other Details:
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Languages: eng Pagination: S14 Citation Subset: IM |
Affiliation:
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Department of Computer Science, Iowa State University, Ames 50011, USA. wcchang@iastate.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Computer Simulation Gene Duplication* Genome, Plant Genomics / methods Phylogeny* Plants / genetics* Programming, Linear* |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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