EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes

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• dc.contributor.author Marcet Houben, Marina
• dc.contributor.author Gabaldón Estevan, Juan Antonio, 1973-
• dc.date.accessioned 2020-03-17T07:33:39Z
• dc.date.available 2020-03-17T07:33:39Z
• dc.date.issued 2020
• dc.description.abstract 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.
• dc.description.sponsorship 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)
• dc.format.mimetype application/pdf
• dc.identifier.citation Marcet-Houben M, Gabaldón T. EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes. Bioinformatics. 2020 Feb 15; 36(4): 1265-1266. DOI: 10.1093/bioinformatics/btz706
• dc.identifier.doi http://dx.doi.org/10.1093/bioinformatics/btz706
• dc.identifier.issn 1367-4803
• dc.identifier.uri http://hdl.handle.net/10230/43909
• dc.language.iso eng
• dc.publisher Oxford University Press
• dc.relation.ispartof Bioinformatics. 2020 Feb 15; 36(4): 1265-6
• dc.relation.projectID info:eu-repo/grantAgreement/ES/1PE/BFU2015-67107
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/724173
• dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/642095
• dc.rights © 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 cited
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
• dc.subject.other Genètica
• dc.subject.other Genòmica
• dc.subject.other Gens
• dc.subject.other Cèl·lules eucariotes
• dc.title EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion