EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes

MOTIVATION: The evolution and role of gene clusters in eukaryotes is poorly understood. Currently, most studies and computational prediction programs limit their focus to specific types of clusters, such as those involved in secondary metabolism. RESULTS: We present EvolClust, a python-based tool fo...

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Detalles Bibliográficos
Autores: Marcet Houben, Marina, Gabaldón Estevan, Juan Antonio, 1973-
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/43909
Acceso en línea:http://hdl.handle.net/10230/43909
http://dx.doi.org/10.1093/bioinformatics/btz706
Access Level:acceso abierto
Palabra clave:Genètica
Genòmica
Gens
Cèl·lules eucariotes
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oai_identifier_str oai:recercat.cat:10230/43909
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repository_id_str
spelling EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotesMarcet Houben, MarinaGabaldón Estevan, Juan Antonio, 1973-GenèticaGenòmicaGensCèl·lules eucariotesMOTIVATION: The evolution and role of gene clusters in eukaryotes is poorly understood. Currently, most studies and computational prediction programs limit their focus to specific types of clusters, such as those involved in secondary metabolism. RESULTS: We present EvolClust, a python-based tool for the inference of evolutionary conserved gene clusters from genome comparisons, independently of the function or gene composition of the cluster. EvolClust predicts conserved gene clusters from pairwise genome comparisons and infers families of related clusters from multiple (all versus all) genome comparisons. AVAILABILITY AND IMPLEMENTATION: https://github.com/Gabaldonlab/EvolClust/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) for the EMBL partnership and grants ‘Centro de Excelencia Severo Ochoa’ SEV-2012-0208 and BFU2015-67107 cofounded by European Regional Development Fund (ERDF); from the CERCA Programme/Generalitat de Catalunya; from the Catalan Research Agency (AGAUR) SGR857 and grant from the European Union’s Horizon 2020 research and innovation programme under the grant agreement ERC-2016-724173 the Marie Sklodowska-Curie grant agreement No H2020-MSCA-ITN-2014-642095. The group also receives support from a INB Grant (PT17/0009/0023–ISCIII-SGEFI/ERDF)Oxford University Press202020202020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/43909http://dx.doi.org/10.1093/bioinformatics/btz706reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésBioinformatics. 2020 Feb 15; 36(4): 1265-6info:eu-repo/grantAgreement/ES/1PE/BFU2015-67107info:eu-repo/grantAgreement/EC/H2020/724173info:eu-repo/grantAgreement/EC/H2020/642095© 2019 Marina Marcet-Houben, Toni Gabaldón. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License,which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly citedhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/439092026-05-29T05:05:01Z
dc.title.none.fl_str_mv EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
title EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
spellingShingle EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
Marcet Houben, Marina
Genètica
Genòmica
Gens
Cèl·lules eucariotes
title_short EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
title_full EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
title_fullStr EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
title_full_unstemmed EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
title_sort EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
dc.creator.none.fl_str_mv Marcet Houben, Marina
Gabaldón Estevan, Juan Antonio, 1973-
author Marcet Houben, Marina
author_facet Marcet Houben, Marina
Gabaldón Estevan, Juan Antonio, 1973-
author_role author
author2 Gabaldón Estevan, Juan Antonio, 1973-
author2_role author
dc.subject.none.fl_str_mv Genètica
Genòmica
Gens
Cèl·lules eucariotes
topic Genètica
Genòmica
Gens
Cèl·lules eucariotes
description MOTIVATION: The evolution and role of gene clusters in eukaryotes is poorly understood. Currently, most studies and computational prediction programs limit their focus to specific types of clusters, such as those involved in secondary metabolism. RESULTS: We present EvolClust, a python-based tool for the inference of evolutionary conserved gene clusters from genome comparisons, independently of the function or gene composition of the cluster. EvolClust predicts conserved gene clusters from pairwise genome comparisons and infers families of related clusters from multiple (all versus all) genome comparisons. AVAILABILITY AND IMPLEMENTATION: https://github.com/Gabaldonlab/EvolClust/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/43909
http://dx.doi.org/10.1093/bioinformatics/btz706
url http://hdl.handle.net/10230/43909
http://dx.doi.org/10.1093/bioinformatics/btz706
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Bioinformatics. 2020 Feb 15; 36(4): 1265-6
info:eu-repo/grantAgreement/ES/1PE/BFU2015-67107
info:eu-repo/grantAgreement/EC/H2020/724173
info:eu-repo/grantAgreement/EC/H2020/642095
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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