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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Detalhes bibliográficos
Autores: Marcet Houben, Marina, Gabaldón Estevan, Juan Antonio, 1973-
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Recursos:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/43909
Acesso em linha:http://hdl.handle.net/10230/43909
http://dx.doi.org/10.1093/bioinformatics/btz706
Access Level:acceso abierto
Palavra-chave:Genètica
Genòmica
Gens
Cèl·lules eucariotes
Descrição
Resumo: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.