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BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts
Various types of genome and gene similarity networks along with their characteristics have been increasingly used for retracing different kinds of evolutionary and ecological relationships. Here, we present a new polynomial time algorithm and the corresponding software (BRIDES) to provide characteri...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007014/ https://www.ncbi.nlm.nih.gov/pubmed/27580188 http://dx.doi.org/10.1371/journal.pone.0161474 |
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author | Lord, Etienne Le Cam, Margaux Bapteste, Éric Méheust, Raphaël Makarenkov, Vladimir Lapointe, François-Joseph |
author_facet | Lord, Etienne Le Cam, Margaux Bapteste, Éric Méheust, Raphaël Makarenkov, Vladimir Lapointe, François-Joseph |
author_sort | Lord, Etienne |
collection | PubMed |
description | Various types of genome and gene similarity networks along with their characteristics have been increasingly used for retracing different kinds of evolutionary and ecological relationships. Here, we present a new polynomial time algorithm and the corresponding software (BRIDES) to provide characterization of different types of paths existing in evolving (or augmented) similarity networks under the constraint that such paths contain at least one node that was not present in the original network. These different paths are denoted as Breakthroughs, Roadblocks, Impasses, Detours, Equal paths, and Shortcuts. The analysis of their distribution can allow discriminating among different evolutionary hypotheses concerning genomes or genes at hand. Our approach is based on an original application of the popular shortest path Dijkstra’s and Yen’s algorithms. The C++ and R versions of the BRIDES program are freely available at: https://github.com/etiennelord/BRIDES. |
format | Online Article Text |
id | pubmed-5007014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-50070142016-09-27 BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts Lord, Etienne Le Cam, Margaux Bapteste, Éric Méheust, Raphaël Makarenkov, Vladimir Lapointe, François-Joseph PLoS One Research Article Various types of genome and gene similarity networks along with their characteristics have been increasingly used for retracing different kinds of evolutionary and ecological relationships. Here, we present a new polynomial time algorithm and the corresponding software (BRIDES) to provide characterization of different types of paths existing in evolving (or augmented) similarity networks under the constraint that such paths contain at least one node that was not present in the original network. These different paths are denoted as Breakthroughs, Roadblocks, Impasses, Detours, Equal paths, and Shortcuts. The analysis of their distribution can allow discriminating among different evolutionary hypotheses concerning genomes or genes at hand. Our approach is based on an original application of the popular shortest path Dijkstra’s and Yen’s algorithms. The C++ and R versions of the BRIDES program are freely available at: https://github.com/etiennelord/BRIDES. Public Library of Science 2016-08-31 /pmc/articles/PMC5007014/ /pubmed/27580188 http://dx.doi.org/10.1371/journal.pone.0161474 Text en © 2016 Lord et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Lord, Etienne Le Cam, Margaux Bapteste, Éric Méheust, Raphaël Makarenkov, Vladimir Lapointe, François-Joseph BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title | BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title_full | BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title_fullStr | BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title_full_unstemmed | BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title_short | BRIDES: A New Fast Algorithm and Software for Characterizing Evolving Similarity Networks Using Breakthroughs, Roadblocks, Impasses, Detours, Equals and Shortcuts |
title_sort | brides: a new fast algorithm and software for characterizing evolving similarity networks using breakthroughs, roadblocks, impasses, detours, equals and shortcuts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5007014/ https://www.ncbi.nlm.nih.gov/pubmed/27580188 http://dx.doi.org/10.1371/journal.pone.0161474 |
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