ChEBI in 2016: Improved services and an expanding collection of metabolites

By Janna Hastings, Gareth Owen, Adriano Dekker, Marcus Ennis, Namrata Kale, Venkatesh Muthukrishnan, Steve Turner, Neil Swainston, Pedro Mendes, Christoph Steinbeck. 2015

1,026 citations recorded by the source corpus.

ChEBI is a database and ontology containing information about chemical entities of biological interest. It currently includes over 46 000 entries, each of which is classified within the ontology and assigned multiple annotations including (where relevant) a chemical structure, database cross-references, synonyms and literature citations. All content is freely available and can be accessed online at http://www.ebi.ac.uk/chebi. In this update paper, we describe recent improvements and additions to the ChEBI offering. We have substantially extended our collection of endogenous metabolites for several organisms including human, mouse, Escherichia coli and yeast. Our front-end has also been reworked and updated, improving the user experience, removing our dependency on Java applets in favour of embedded JavaScript components and moving from a monthly release update to a ‘live’ website. Programmatic access has been improved by the introduction of a library, libChEBI, in Java, Python and Matlab. Furthermore, we have added two new tools, namely an analysis tool, BiNChE, and a query tool for the ontology, OntoQuery.

Subfields: Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

Citations in the corpus

UniProt: a worldwide hub of protein knowledge (2018, background): “…scientific publications is stored in the UniProtKB / Swiss-Prot section of the UniProt Knowledgebase and describes functional information both in the form of human readable free-text / controlled syntax summaries and via structured vocabularies such as the Gene Ontology (GO) (15) or ChEBI (16).”
SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets (2022, background): “, ChEMBL [21], ChEBI [22], DrugBank [23], BindingDB [24], PharmGKB [25], Guide to Pharmacology [26], Selleck, and ZINC [27]), and drug target profiles from MICHA [28].”
UniProt: the universal protein knowledgebase in 2021 (2020, methodology): “Rhea (14) uses the chemical ontology ChEBI (Chemical Entities of Biological Interest) (15) to describe reaction participants, their chemical structures and chemical transformations.”
FlyBase: a guided tour of highlighted features (2022, background): “Hastings J, Owen G, Dekker A, Ennis M, Kale N, Muthukrishnan V, Turner S, Swainston N, Mendes P, Steinbeck C. ChEBI in 2016: improved services and an expanding collection of metabolites.”
MetaboLights: a resource evolving in response to the needs of its scientific community (2019, background): “com/MSI-Metabolomics-Standards-Initiative/MSIO) Metabolites Chemical Entities of Biological Interest (ChEBI) (2)”
FlyBase: updates to the Drosophila genes and genomes database (2024, neutral): “2023), which has a wider range of chemicals and more links to external databases, and ChEBI (Hastings et al .”
Protein Ontology (PRO): enhancing and scaling up the representation of protein entities (2016, background): “org/), Chemical Entities of Biological Interest (ChEBI) (14), and UniProt.”
UniProt: the Universal Protein Knowledgebase in 2023 (2022, methodology): “We continued the standardisation of all small molecule annotations in UniProtKB using the chemical ontology ChEBI (8), focusing on biologically relevant (or ‘cognate’) ligands such as activators, inhibitors, and cofactors and their corresponding binding sites, knowledge of which is captured from the”
The Gene Ontology resource: enriching a GOld mine (2020, methodology): “Rhea uses ChEBI (13) to precisely describe each reaction’s participants and their chemical structures (14).”
RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning (2022, neutral): “ChEBI (73) Chemical entities of biological interest”
MetaboLights: open data repository for metabolomics (2023, background): “Reuse of data deposited to MetaboLights often starts during curation, where metabolite names are assigned a database identifier with ChEBI (Chemical Entities of Biological Inter-est) ( https:// www.ebi.ac.uk/ chebi ) ( 17 ).”
The reactome pathway knowledgebase (2019, background): “As shown for the antithrombotic chemical apixaban in Figure 1A, each chemical drug instance is mapped to its counterpart in IUPHAR (8) and if one is available in ChEBI (9) and for additional pharmacological data.”