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Inferring duplication episodes from unrooted gene trees

BACKGROUND: One of evolutionary molecular biology fundamental issues is to discover genomic duplication events and their correspondence to the species tree. Such events can be reconstructed by clustering single gene duplications inferred by reconciling a set of gene trees with a species tree. RESULT...

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Autores principales: Paszek, Jarosław, Górecki, Paweł
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998884/
https://www.ncbi.nlm.nih.gov/pubmed/29745844
http://dx.doi.org/10.1186/s12864-018-4623-z
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author Paszek, Jarosław
Górecki, Paweł
author_facet Paszek, Jarosław
Górecki, Paweł
author_sort Paszek, Jarosław
collection PubMed
description BACKGROUND: One of evolutionary molecular biology fundamental issues is to discover genomic duplication events and their correspondence to the species tree. Such events can be reconstructed by clustering single gene duplications inferred by reconciling a set of gene trees with a species tree. RESULTS: Here we propose the first solutions to the genomic duplication problem in which every reconciliation with the minimal number of single gene duplications is allowed and the method of clustering called minimum episodes under the assumption that input gene trees are unrooted. CONCLUSIONS: We showed new theoretical properties of unrooted reconciliation for the duplication cost and apply them to design several exact and heuristic algorithms for solving the problem. Our evaluation study on empirical dataset confirmed several genomic duplication events from the literature and demonstrate that algorithms can be successfully applied.
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spelling pubmed-59988842018-06-25 Inferring duplication episodes from unrooted gene trees Paszek, Jarosław Górecki, Paweł BMC Genomics Research BACKGROUND: One of evolutionary molecular biology fundamental issues is to discover genomic duplication events and their correspondence to the species tree. Such events can be reconstructed by clustering single gene duplications inferred by reconciling a set of gene trees with a species tree. RESULTS: Here we propose the first solutions to the genomic duplication problem in which every reconciliation with the minimal number of single gene duplications is allowed and the method of clustering called minimum episodes under the assumption that input gene trees are unrooted. CONCLUSIONS: We showed new theoretical properties of unrooted reconciliation for the duplication cost and apply them to design several exact and heuristic algorithms for solving the problem. Our evaluation study on empirical dataset confirmed several genomic duplication events from the literature and demonstrate that algorithms can be successfully applied. BioMed Central 2018-05-08 /pmc/articles/PMC5998884/ /pubmed/29745844 http://dx.doi.org/10.1186/s12864-018-4623-z Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Paszek, Jarosław
Górecki, Paweł
Inferring duplication episodes from unrooted gene trees
title Inferring duplication episodes from unrooted gene trees
title_full Inferring duplication episodes from unrooted gene trees
title_fullStr Inferring duplication episodes from unrooted gene trees
title_full_unstemmed Inferring duplication episodes from unrooted gene trees
title_short Inferring duplication episodes from unrooted gene trees
title_sort inferring duplication episodes from unrooted gene trees
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998884/
https://www.ncbi.nlm.nih.gov/pubmed/29745844
http://dx.doi.org/10.1186/s12864-018-4623-z
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