Rhea, the reaction knowledgebase in 2022

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Abstract

Rhea ( https://www.rhea-db.org) is an expert-curated knowledgebase of biochemical reactions based on the chemical ontology ChEBI (Chemical Entities of Biological Interest) ( https://www.ebi.ac.uk/chebi). In this paper, we describe a number of key developments in Rhea since our last report in the database issue of Nucleic Acids Research in 2019. These include improved reaction coverage in Rhea, the adoption of Rhea as the reference vocabulary for enzyme annotation in the UniProt knowledgebase UniProtKB ( https://www.uniprot.org), the development of a new Rhea website, and the designation of Rhea as an ELIXIR Core Data Resource. We hope that these and other developments will enhance the utility of Rhea as a reference resource to study and engineer enzymes and the metabolic systems in which they function.

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Most cited references 50

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UniProt: the universal protein knowledgebase in 2021

(2020)

Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

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KEGG: integrating viruses and cellular organisms

Minoru Kanehisa, Miho Furumichi, Yoko Sato … (2020)

Abstract KEGG (https://www.kegg.jp/) is a manually curated resource integrating eighteen databases categorized into systems, genomic, chemical and health information. It also provides KEGG mapping tools, which enable understanding of cellular and organism-level functions from genome sequences and other molecular datasets. KEGG mapping is a predictive method of reconstructing molecular network systems from molecular building blocks based on the concept of functional orthologs. Since the introduction of the KEGG NETWORK database, various diseases have been associated with network variants, which are perturbed molecular networks caused by human gene variants, viruses, other pathogens and environmental factors. The network variation maps are created as aligned sets of related networks showing, for example, how different viruses inhibit or activate specific cellular signaling pathways. The KEGG pathway maps are now integrated with network variation maps in the NETWORK database, as well as with conserved functional units of KEGG modules and reaction modules in the MODULE database. The KO database for functional orthologs continues to be improved and virus KOs are being expanded for better understanding of virus-cell interactions and for enabling prediction of viral perturbations.

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The Gene Ontology resource: enriching a GOld mine

Jurg Bahler, Christopher Tabone (2021)

Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

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Author and article information

Contributors

Parit Bansal:

ORCID: https://orcid.org/0000-0002-0875-1680

Anne Morgat:

ORCID: https://orcid.org/0000-0002-1216-2969

Kristian B Axelsen:

ORCID: https://orcid.org/0000-0003-3889-2879

Venkatesh Muthukrishnan:

ORCID: https://orcid.org/0000-0002-6850-9888

Elisabeth Coudert:

ORCID: https://orcid.org/0000-0001-8314-404X

Lucila Aimo:

ORCID: https://orcid.org/0000-0003-0943-6401

Nevila Hyka-Nouspikel:

ORCID: https://orcid.org/0000-0001-7855-209X

Elisabeth Gasteiger:

ORCID: https://orcid.org/0000-0003-1829-162X

Arnaud Kerhornou:

ORCID: https://orcid.org/0000-0002-2890-295X

Teresa Batista Neto:

ORCID: https://orcid.org/0000-0003-4543-637X

Monica Pozzato:

ORCID: https://orcid.org/0000-0002-3080-5243

Marie-Claude Blatter:

ORCID: https://orcid.org/0000-0002-7474-1499

Alex Ignatchenko:

ORCID: https://orcid.org/0000-0002-6083-941X

Nicole Redaschi:

ORCID: https://orcid.org/0000-0001-8890-2268

Alan Bridge:

ORCID: https://orcid.org/0000-0003-2148-9135

Journal

Journal ID (nlm-ta): Nucleic Acids Res

Journal ID (iso-abbrev): Nucleic Acids Res

Journal ID (publisher-id): nar

Title: Nucleic Acids Research

Publisher: Oxford University Press

ISSN (Print): 0305-1048

ISSN (Electronic): 1362-4962

Publication date Collection: 07 January 2022

Publication date (Electronic): 10 November 2021

Publication date PMC-release: 10 November 2021

Volume: 50

Issue: D1

Pages: D693-D700

Affiliations

Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire , CH-1211 Geneva 4, Switzerland

EMBL-EBI European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus , Hinxton, Cambridge CB10 1SD, UK

Swiss-Prot group, SIB Swiss Institute of Bioinformatics, Centre Medical Universitaire , CH-1211 Geneva 4, Switzerland

Author notes

To whom correspondence should be addressed. Tel: +41 22 379 41 79; Email: alan.bridge@ 123456sib.swiss

Correspondence may also be addressed to Parit Bansal. Email: parit.bansal@ 123456sib.swiss

Correspondence may also be addressed to Anne Morgat. Email: anne.morgat@ 123456sib.swiss

The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.

Author information

Parit Bansal https://orcid.org/0000-0002-0875-1680

Anne Morgat https://orcid.org/0000-0002-1216-2969

Kristian B Axelsen https://orcid.org/0000-0003-3889-2879

Venkatesh Muthukrishnan https://orcid.org/0000-0002-6850-9888

Elisabeth Coudert https://orcid.org/0000-0001-8314-404X

Lucila Aimo https://orcid.org/0000-0003-0943-6401

Nevila Hyka-Nouspikel https://orcid.org/0000-0001-7855-209X

Elisabeth Gasteiger https://orcid.org/0000-0003-1829-162X

Arnaud Kerhornou https://orcid.org/0000-0002-2890-295X

Teresa Batista Neto https://orcid.org/0000-0003-4543-637X

Monica Pozzato https://orcid.org/0000-0002-3080-5243

Marie-Claude Blatter https://orcid.org/0000-0002-7474-1499

Alex Ignatchenko https://orcid.org/0000-0002-6083-941X

Nicole Redaschi https://orcid.org/0000-0001-8890-2268

Alan Bridge https://orcid.org/0000-0003-2148-9135

Article

Publisher ID: gkab1016

DOI: 10.1093/nar/gkab1016

PMC ID: 8728268

PubMed ID: 34755880

SO-VID: 7a47c862-d2b1-468b-94e5-0c1b72f87b68

License:

This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date accepted : 09 November 2021

Date revision received : 08 October 2021

Date received : 14 September 2021

Page count

Pages: 8

Funding

Funded by: Swiss Federal Government;

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Rhea, the reaction knowledgebase in 2022

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Most cited references 50

UniProt: the universal protein knowledgebase in 2021

KEGG: integrating viruses and cellular organisms

The Gene Ontology resource: enriching a GOld mine

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Cited by 39

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