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Genome3D: integrating a collaborative data pipeline to expand the depth and breadth of consensus protein structure annotation.

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posted on 22.01.2020 by Ian Sillitoe, Antonina Andreeva, Tom L Blundell, Daniel WA Buchan, Robert D Finn, Julian Gough, David Jones, Lawrence A Kelley, Typhaine Paysan-Lafosse, Su Datt Lam, Alexey G Murzin, Arun Prasad Pandurangan, Gustavo A Salazar, Marcin J Skwark, Michael JE Sternberg, Sameer Velankar, Christine Orengo
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.

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