Open Biological and Biomedical Ontology (OBO) Foundry
The Open Biological and Biomedical Ontology (OBO) Foundry is a collective of ontology developers that are committed to collaboration and adherence to shared principles. The mission of the OBO Foundry is to develop a family of interoperable ontologies that are both logically well-formed and scientifically accurate. To achieve this, OBO Foundry participants voluntarily adhere to and contribute to the development of an evolving set of principles including open use, collaborative development, non-overlapping and strictly-scoped content, and common syntax and relations, based on ontology models that work well, such as the Gene Ontology (GO).
The OBO Foundry is overseen by an Operations Committee with Editorial, Technical and Outreach working groups. The processes of the Editorial working group are modelled on the journal refereeing process. A complete treatment of the OBO Foundry is given in The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration.
On this site you will find a table of ontologies, available in several formats, with details for each, and documentation on OBO Principles.
You can contribute to this site using GitHub OBOFoundry/OBOFoundry.github.io or get in touch with us by joining our mail list https://groups.google.com/forum/#!forum/obo-discuss. Homepage: http://www.obofoundry.org/
An information artifact is, loosely, a dependent continuant or its bearer that is created as the result of one or more intentional processes. Examples: uniprot, the english language, the contents of this document or a printout of it, the temperature measurements from a weather balloon. For more information, see the project home page at link.
The Gene Ontology resource provides a computational representation of our current scientific knowledge about the functions of genes (or, more properly, the protein and non-coding RNA molecules produced by genes) from many different organisms, from humans to bacteria. It is widely used to support scientific research, and has been cited in tens of thousands of publications.
Understanding gene function—how individual genes contribute to the biology of an organism at the molecular, cellular and organism levels—is one of the primary aims of biomedical research. Moreover, experimental knowledge obtained in one organism is often applicable to other organisms, particularly if the organisms share the relevant genes because they inherited them from their common ancestor. The Gene Ontology (GO), as a consortium, began in 1998 when researchers studying the genome of three model organisms—Drosophila melanogaster (fruit fly), Mus musculus (mouse), and Saccharomyces cerevisiae (brewer’s or baker’s yeast)—agreed to work collaboratively on a common classification scheme for gene function, and today the number of different organisms represented in GO is in the thousands. GO makes it possible, in a flexible and dynamic way, to provide comparable descriptions of homologous gene and protein sequences across the phylogenetic spectrum.
GO is also at the hub of a major effort to represent the vast amount of biomedical knowledge in a computable form. GO is linked to many other biomedical ontologies, and is a foundation for research applying computer science in biology and medicine.
The Evidence & Conclusion Ontology (ECO) describes types of scientific evidence within the realm of biological research that can arise from laboratory experiments, computational methods, manual literature curation, and other means. Researchers can use these types of evidence to support assertions about things (such as scientific conclusions, gene annotations, or other statements of fact) that result from scientific research.
ECO comprises two high-level classes, evidence and assertion method, where evidence is defined as “a type of information that is used to support an assertion,” and assertion method is defined as “a means by which a statement is made about an entity.” Together evidence and assertion method can be combined to describe both the support for an assertion and whether that assertion was made by a human being or a computer. However, ECO is not used to make the assertion itself; for that, one would use another ontology, free text description, or some other means.
ECO was originally created around the year 2000 to support gene product annotation by the Gene Ontology, which now displays ECO in AmiGO 2. Today ECO is used by many groups concerned with evidence in scientific research.
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 uses nomenclature, symbolism and terminology endorsed by the following international scientific bodies:
- International Union of Pure and Applied Chemistry (IUPAC)
- Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB)
Molecules directly encoded by the genome (e.g. nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI.
The Basic Formal Ontology (BFO) is a small, upper level ontology that is designed for use in supporting information retrieval, analysis and integration in scientific and other domains. BFO is a genuine upper ontology. Thus it does not contain physical, chemical, biological or other terms which would properly fall within the coverage domains of the special sciences. BFO is used by more than 250 ontology-driven endeavors throughout the world.
The BFO project was initiated in 2002 under the auspices of the project Forms of Life sponsored by the Volkswagen Foundation. The theory behind BFO was developed first by Barry Smith and Pierre Grenon and presented in a series of publications listed here.