MetaPhOrs 2.0: integrative, phylogeny-based inference of orthology and paralogy across the tree of life
Data de publicació
2020ISSN
0305-1048
Resum
Inferring homology relationships across genes in different species is a central task in comparative genomics. Therefore, a large number of resources and methods have been developed over the years. Some public databases include phylogenetic trees of homologous gene families which can be used to further differentiate homology relationships into orthology and paralogy. MetaPhOrs is a web server that integrates phylogenetic information from different sources to provide orthology and paralogy relationships based on a common phylogeny-based predictive algorithm and associated with a consistency-based confidence score. Here we describe the latest version of the web server which includes major new implementations and provides orthology and paralogy relationships derived from ∼8.2 million gene family trees—from 13 different source repositories across ∼4000 species with sequenced genomes.
Tipus de document
Article
Versió del document
Versió publicada
Llengua
Anglès
Matèries (CDU)
5 - Ciències pures i naturals
Pàgines
4
Publicat per
Oxford University Press
Col·lecció
48; W1
Publicat a
Nucleic Acids Research
Citació recomanada
Chorostecki, Uciel; Molina, Manuel; Pryszcz, Leszek P. [et al.]. MetaPhOrs 2.0: integrative, phylogeny-based inference of orthology and paralogy across the tree of life. Nucleic Acids Research, 2020, 48(W1), W553-557. Disponible en: <https://academic.oup.com/nar/article/48/W1/W553/5826172>. Fecha de acceso: 7 feb. 2023. DOI: 10.1093/nar/gkaa282
Número de l'acord de la subvenció
info:eu-repo/grantAgreement/EU/H2020/793699
info:eu-repo/grantAgreement/EU/H2020/724173
Nota
H2020 Marie Skłodowska-Curie Actions [H2020-MSCAIF-2017-793699 to U.C.]; Spanish Ministry of Economy, Industry, and Competitiveness (MEIC) [PGC2018-099921- B-I00]; CERCA Programme/Generalitat de Catalunya; Catalan Research Agency (AGAUR) SGR423; European Union’s Horizon 2020 Research and Innovation Programme [ERC-2016-724173]; INB [PT17/0009/0023 - ISCIII-SGEFI/ERDF to T.G.]. Funding for open access charge: H2020 Grant.
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Drets
© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
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