Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation.
Journal
Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011
Informations de publication
Date de publication:
08 01 2020
08 01 2020
Historique:
accepted:
07
11
2019
revised:
09
10
2019
received:
23
09
2019
pubmed:
17
11
2019
medline:
30
5
2020
entrez:
17
11
2019
Statut:
ppublish
Résumé
Genome3D (https://www.genome3d.eu) is a freely available resource that provides consensus structural annotations for representative protein sequences taken from a selection of model organisms. Since the last NAR update in 2015, the method of data submission has been overhauled, with annotations now being 'pushed' to the database via an API. As a result, contributing groups are now able to manage their own structural annotations, making the resource more flexible and maintainable. The new submission protocol brings a number of additional benefits including: providing instant validation of data and avoiding the requirement to synchronise releases between resources. It also makes it possible to implement the submission of these structural annotations as an automated part of existing internal workflows. In turn, these improvements facilitate Genome3D being opened up to new prediction algorithms and groups. For the latest release of Genome3D (v2.1), the underlying dataset of sequences used as prediction targets has been updated using the latest reference proteomes available in UniProtKB. A number of new reference proteomes have also been added of particular interest to the wider scientific community: cow, pig, wheat and mycobacterium tuberculosis. These additions, along with improvements to the underlying predictions from contributing resources, has ensured that the number of annotations in Genome3D has nearly doubled since the last NAR update article. The new API has also been used to facilitate the dissemination of Genome3D data into InterPro, thereby widening the visibility of both the annotation data and annotation algorithms.
Identifiants
pubmed: 31733063
pii: 5626529
doi: 10.1093/nar/gkz967
pmc: PMC7139969
doi:
Substances chimiques
Proteins
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
D314-D319Subventions
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/N019431/1
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/K020013/1
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/M011712/1
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/M011526/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U105192716
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/N019172/1
Pays : United Kingdom
Informations de copyright
© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
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