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"An ontology is a formal representation of a body of knowledges within a given domain. Ontologies usually consist of a set of classes (or terms or concepts) with relations that operate between them."
These are the various terminologies used to create annotations.
Name | Code | Type | Update / Version | Description | Link |
---|---|---|---|---|---|
ATC | ATC | Drugs | 2019-11-04 | This ontology is a representation of the ATC classification used for the classification of drugs and provided by WHO (World Health Organization). Based on the ATC code of the main ingredient of a product, this medical product can be classify in the ATC system. | ATC |
Drugbank | DB | Drugs | 2020-01-03 | The Drugbank database is a freely accessible resource which includes more than 13,000 records (version 5.1.4, released 2019-07-20). It contains information on drugs and drug targets, synonyms and product names. | Drugbank |
NCI Thesaurus | NCI | Disease | 2019-11-25 | The NCI Thesaurus (NCIt) is used for disease mapping. It covers clinical care, translational and basic research, public information and administrative activities. Provided by the National Cancer Institute, this terminology is a standard for biomedical coding and reference, used both by public and private scientific partners worldwide. This NCI's reference terminology contains the NCI_CUI, the semantic type, a prefered term, some NCI and MeSH synonyms. | NCIt |
ICD-O-3 | ICDO | Disease | 2019-06-21 v3.1 |
The International Classification of Diseases Oncology (ICD-O) is a biomedical ontology for logical representation of the terms and relations related to the International Classification of Diseases (ICD). | ICD-O-3 |
MeSH | MH | MeSH | 2018-12-01 | The Medical Subject Headings (MeSH), provided by the U.S. National Library of Medicine (NLM), is a controlled vocabulary thesaurus used for indexing articles for PubMed. In comparison with specialzed ontologies like the NCIt, MeSH is less granular and easily identified by Natural Language Processing thanks to synonyms. | MeSH |
Gene Ontology | GO | GO | 2020-01-01 | The Gene Ontology (GO) knowledgebase is the world's largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research. | Gene Ontology |
neXtProt | NP | Human Gene | 2020-01-10 | Developed by the SIB (Swiss Institute of Bioinformatics) in 2008, the neXtProt human protein knowledgebase is a comprehensive human-centric discovery platform. More than 20,000 proteins were manually annotated and still updated. The provides to researchers a high-quality synonym for both protein and gene names. | neXtProt |
UniProtKB/SwissProt | UP | Gene | 2018-04-10 | The UniProt Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins, with accurate, consistent and rich annotation. We used the Reviewed subset UinProtKB/Swiss-Prot which includes records with information extracted from literature and curator-evaluated computational analysis. | UniProtKB/SwissProt |
Species | SPEC | Species | 2019-04-15 | This terminology was created by the team and includes many species and related code from NCBI taxonomy collection. | NCBI Taxonomy |
CheBI | CH | Chemical Entities of Biological Interest | 2020-01-13 | Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The term ‘molecular entity’ refers to any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms. ChEBI incorporates an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. | ChEBI |
ECO | ECO | Scientific evidence | 2020-01-14 | The Evidence & Conclusion Ontology (ECO) describes types of scientific evidence within the biological research domain that arise from laboratory experiments, computational methods, literature curation, or other means. | ECO |
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