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The multiple gene duplication problem revisited
Motivation: Deciphering the location of gene duplications and multiple gene duplication episodes on the Tree of Life is fundamental to understanding the way gene families and genomes evolve. The multiple gene duplication problem provides a framework for placing gene duplication events onto nodes of...
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2718628/ https://www.ncbi.nlm.nih.gov/pubmed/18586705 http://dx.doi.org/10.1093/bioinformatics/btn150 |
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author | Bansal, Mukul S. Eulenstein, Oliver |
author_facet | Bansal, Mukul S. Eulenstein, Oliver |
author_sort | Bansal, Mukul S. |
collection | PubMed |
description | Motivation: Deciphering the location of gene duplications and multiple gene duplication episodes on the Tree of Life is fundamental to understanding the way gene families and genomes evolve. The multiple gene duplication problem provides a framework for placing gene duplication events onto nodes of a given species tree, and detecting episodes of multiple gene duplication. One version of the multiple gene duplication problem was defined by Guigó et al. in 1996. Several heuristic solutions have since been proposed for this problem, but no exact algorithms were known. Results: In this article we solve this longstanding open problem by providing the first exact and efficient solution. We also demonstrate the improvement offered by our algorithm over the best heuristic approaches, by applying it to several simulated as well as empirical datasets. Contact: oeulenst@cs.iastate.edu |
format | Text |
id | pubmed-2718628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-27186282009-07-31 The multiple gene duplication problem revisited Bansal, Mukul S. Eulenstein, Oliver Bioinformatics Ismb 2008 Conference Proceedings 19–23 July 2008, Toronto Motivation: Deciphering the location of gene duplications and multiple gene duplication episodes on the Tree of Life is fundamental to understanding the way gene families and genomes evolve. The multiple gene duplication problem provides a framework for placing gene duplication events onto nodes of a given species tree, and detecting episodes of multiple gene duplication. One version of the multiple gene duplication problem was defined by Guigó et al. in 1996. Several heuristic solutions have since been proposed for this problem, but no exact algorithms were known. Results: In this article we solve this longstanding open problem by providing the first exact and efficient solution. We also demonstrate the improvement offered by our algorithm over the best heuristic approaches, by applying it to several simulated as well as empirical datasets. Contact: oeulenst@cs.iastate.edu Oxford University Press 2008-07-01 /pmc/articles/PMC2718628/ /pubmed/18586705 http://dx.doi.org/10.1093/bioinformatics/btn150 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Ismb 2008 Conference Proceedings 19–23 July 2008, Toronto Bansal, Mukul S. Eulenstein, Oliver The multiple gene duplication problem revisited |
title | The multiple gene duplication problem revisited |
title_full | The multiple gene duplication problem revisited |
title_fullStr | The multiple gene duplication problem revisited |
title_full_unstemmed | The multiple gene duplication problem revisited |
title_short | The multiple gene duplication problem revisited |
title_sort | multiple gene duplication problem revisited |
topic | Ismb 2008 Conference Proceedings 19–23 July 2008, Toronto |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2718628/ https://www.ncbi.nlm.nih.gov/pubmed/18586705 http://dx.doi.org/10.1093/bioinformatics/btn150 |
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