ArticleNucleic acids research2019
Updates in Rhea: SPARQLing biochemical reaction data.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed.
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- Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP.Nature communications · 2022Article
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- Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content.Applied in vitro toxicology · 2022Article
- The reactome pathway knowledgebase 2022.Nucleic acids research · 2022Article
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- Rhea, the reaction knowledgebase in 2022.Nucleic acids research · 2022Article
- The Immunometabolic Atlas: A tool for design and interpretation of metabolomics studies in immunology.PloS one · 2022Article
- Data-Driven Synthetic Cell Factories Development for Industrial Biomanufacturing.Biodesign research · 2022Review
- PyMiner: A method for metabolic pathway design based on the uniform similarity of substrate-product pairs and conditional search.PloS one · 2022Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rhea (http://www.rhea-db.org) is a comprehensive and non-redundant resource of over 11 000 expert-curated biochemical reactions that uses chemical entities from the ChEBI ontology to represent reaction participants. Originally designed as an annotation vocabulary for the UniProt Knowledgebase (UniProtKB), Rhea also provides reaction data for a range of other core knowledgebases and data repositories including ChEBI and MetaboLights. Here we describe recent developments in Rhea, focusing on a new resource description framework representation of Rhea reaction data and an SPARQL endpoint (https://sparql.rhea-db.org/sparql) that provides access to it. We demonstrate how federated queries that combine the Rhea SPARQL endpoint and other SPARQL endpoints such as that of UniProt can provide improved metabolite annotation and support integrative analyses that link the metabolome through the proteome to the transcriptome and genome. These developments will significantly boost the utility of Rhea as a means to link chemistry and biology for a more holistic understanding of biological systems and their function in health and disease.
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