ChEBI: a database and ontology for chemical entities of biological interest (original) (raw)
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Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology
BMC Genomics, 2013
Background: The Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI. Results: We have examined and integrated the ChEBI structural hierarchy into the GO resource through computationally-assisted manual curation of both GO and ChEBI. Our work has resulted in the creation of computable definitions of GO terms that contain fully defined semantic relationships to corresponding chemical terms in ChEBI.
ChemFOnt: the chemical functional ontology resource
Nucleic Acids Research
The Chemical Functional Ontology (ChemFOnt), located at https://www.chemfont.ca, is a hierarchical, OWL-compatible ontology describing the functions and actions of >341 000 biologically important chemicals. These include primary metabolites, secondary metabolites, natural products, food chemicals, synthetic food additives, drugs, herbicides, pesticides and environmental chemicals. ChemFOnt is a FAIR-compliant resource intended to bring the same rigor, standardization and formal structure to the terms and terminology used in biochemistry, food chemistry and environmental chemistry as the gene ontology (GO) has brought to molecular biology. ChemFOnt is available as both a freely accessible, web-enabled database and a downloadable Web Ontology Language (OWL) file. Users may download and deploy ChemFOnt within their own chemical databases or integrate ChemFOnt into their own analytical software to generate machine readable relationships that can be used to make new inferences, enrich...
Semantic access to chemistry data with the ChEBI ontology and web services
The Chemical Entities of Biological Interest (ChEBI) ontology is an ontology of chemical entities and their roles, being developed at the European Bioinformatics Institute (EBI). Recent developments include a submission tool for direct user submissions and enhancements to the search facilities available by web services.
Chemical vocabularies and ontologies for bioinformatics
Proceedings of the 2003 International Chemical Information Conference, 2003
The diversity of objects and concepts in biological chemistry can be reflected in the number of ways used to describe an ‘elementary’ biochemical event such as enzymatic reaction. The terminology used in publications or biological databases is often a mixture of terms borrowed from widely different or even contradictory classifications. The ever-growing knowledge cannot be processed meaningfully (e.g. efficiently and correctly referenced in biological databases) without organisation, from controlled vocabularies to dictionaries and thesauri to taxonomies and formal ontologies. Ontology of some domain of knowledge is a controlled vocabulary of terms with defined logical relationships to each other. The unique types of relationships between terms have to be included in biochemical ontologies. The relevance of chemical thesauri and ontologies to bioinformatics is illustrated by current resources and projects at the European Bioinformatics Institute, such as IntEnz (Enzyme Nomenclature), COMe (the bioinorganic motif database) and the IUPHAR Receptor Database.
ChEBI: An open bioinformatics and cheminformatics resource
Current Protocols in Bioinformatics, 2009
Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on “small” chemical compounds. This unit provides a detailed guide to browsing, searching, downloading, and programmatic access to the ChEBI database.
BiNChE: A web tool and library for chemical enrichment analysis based on the ChEBI ontology
BMC Bioinformatics, 2015
Background: Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. Results: We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. Conclusions: BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.
PLoS ONE, 2011
Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at
Ontologies in Medicinal Chemistry: Current Status and Future Challenges
Current Topics in Medicinal Chemistry, 2013
Recent years have seen a dramatic increase in the amount and availability of data in the diverse areas of medicinal chemistry, making it possible to achieve significant advances in fields such as the design, synthesis and biological evaluation of compounds. However, with this data explosion, the storage, management and analysis of available data to extract relevant information has become even a more complex task that offers challenging research issues to Artificial Intelligence (AI) scientists. Ontologies have emerged in AI as a key tool to formally represent and semantically organize aspects of the real world. Beyond glossaries or thesauri, ontologies facilitate communication between experts and allow the application of computational techniques to extract useful information from available data. In medicinal chemistry, multiple ontologies have been developed during the last years which contain knowledge about chemical compounds and processes of synthesis of pharmaceutical products. This article reviews the principal standards and ontologies in medicinal chemistry, analyzes their main applications and suggests future directions.
A Database for Chemical Proteomics: ChEBI
Methods in Molecular Biology, 2011
Small molecules play an important role in chemical proteomics which is concerned with the identification of protein targets interacting with small molecules. Hence the availability of a high quality and free resource storing small molecules is essential for the future development of the field. The Chemical Entities of Biological Interest (ChEBI) database is one such database. The scope of ChEBI includes any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. These entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms. In addition, ChEBI contains a chemical ontology which relates the small molecules with each other thereby making it easier for users to discover data. The ontology also describes the biological roles that the small molecules are active in. The ChEBI database also provides a central reference point in which to access a variety of bioinformatics data points such as pathways and their biochemical reactions; expression data; protein sequence and structures.