Extension and integration of the gene ontology (GO): combining GO vocabularies with external vocabularies.

By David P. Hill, Judith A. Blake, J. Richardson, M. Ringwald. 2002

111 citations recorded by the source corpus.

Structured vocabulary development enhances the management of information in biological databases. As information grows, handling the complexity of vocabularies becomes difficult. Defined methods are needed to manipulate, expand and integrate complex vocabularies. The Gene Ontology (GO) project provides the scientific community with a set of structured vocabularies to describe domains of molecular biology. The vocabularies are used for annotation of gene products and for computational annotation of sequence data sets. The vocabularies focus on three concepts universal to living systems, biological process, molecular function and cellular component. As the vocabularies expand to incorporate terms needed by diverse annotation communities, species-specific terms become problematic. In particular, the use of species-specific anatomical concepts remains unresolved. We present a method for expansion of GO into areas outside of the three original universal concept domains. We combine concepts from two orthogonal vocabularies to generate a larger, more specific vocabulary. The example of mammalian heart development is presented because it addresses two issues that challenge GO; inclusion of organism-specific anatomical terms, and proliferation of terms and relationships. The combination of concepts from orthogonal vocabularies provides a robust representation of relevant terms and an opportunity for evaluation of hypothetical concepts.

Subfields: Molecular Biology

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Citations in the corpus

The Gene Ontology Resource: 20 years and still GOing strong (2018, background): “GO utilizes the structure of external ontologies to aid in reasoning and in the automatic inference of relations between GO terms (13).”
The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology (2004, background): “Tel: +44 1223 494465; Fax: +44 1223 494468; Email: goa@ebi.ac.uk D262–D266 Nucleic Acids Research, 2004, Vol. 32, Database issue DOI: 10.1093/nar/gkh021 initiators, Mouse Genome Database (MGD) (8), FlyBase (9) and Saccharomyces Genome Database (SGD) (10).”
The Gene Ontology: enhancements for 2011 (2011, background): “Formally cross-referencing terms from external ontologies is a powerful way to integrate expertise from different specialist communities into an existing ontology (8,9).”
The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability (2016, background): “The domain and content of CL is intended to be orthogonal to other Foundry ontologies to allow for the construction of compositional classes via logical definitions, as exemplified by the Gene Ontology (GO) [3, 6 – 8].”
Semantic similarity methods in wordNet and their application to information retrieval on the web (2005, background): “Examples of domain specific ontologies include among others ontologies designed around (a) medical concepts such as UMLS [33], SNOMED, MESH [32], (b) genomic data such as GO [6, 13] and (c) spatial data such as SDTS.”
ELM server: a new resource for investigating short functional sites in modular eukaryotic proteins (2003, methodology): “Gene Ontology (GO) identifiers are used for cell compartment, molecular function and biological process (15,16) while the NCBI taxonomy database identifiers (17) are used for taxonomic nodes at the apex of phylogenetic groupings in which an ELM occurs.”
Ontological realism: A methodology for coordinated evolution of scientific ontologies (2010, unknown): “The methodology is described in detail in Hill et al. (2008), which makes clear the essential interplay between the two kinds of descriptions referred to already above of (i) the individual entities observed in the lab and captured in reports of experiments, and (ii) the types these entities instant”