PhenoGO is a computed database designed for high throughput mining that provides phenotypic and experimental context, such as the cell type, disease, tissue and organ to existing annotations between gene products and Gene Ontology (GO) terms as specified in the Gene Ontology Annotations (GOA) for multiple model organisms. For example of mined derivative, see "Discovery of Protein Interaction Networks Shared by Diseases. Pac Symp Biocomp 12:76-87(2007)

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<resource blueprint="true" disco_id="229" full_name="PhenoGO adds phenotypic contextual information to existing associations between gene products and Gene Ontology (GO) terms as specified in GO Annotations (GOA). PhenoGO utilizes an existing Natural Language Processing (NLP) system, called BioMedLEE, an existing knowledge-based phenotype organizer system (PhenOS) in conjunction with MeSH indexing and established biomedical ontologies. The system also encodes the context to identifiers that are associated in different biomedical ontologies, including the UMLS, Cell Ontology, Mouse Anatomy, NCBI taxonomy, GO, and Mammalian Phenotype Ontology. In addition, PhenoGO was evaluated for coding of anatomical and cellular information and assigning the coded phenotypes to the correct GOA; results obtained show that PhenoGO has a precision of 91 and recall of 92, demonstrating that the PhenoGO NLP system can accurately encode a large number of anatomical and cellular ontologies to GO annotations. The PhenoGO Database may be accessed at www.phenogo.org." last-discoed="2009-08-29" nif_id="new" short_name="PhenoGO" url="http://www.phenogo.org">

<parent_organization full_name="MAGNet" />

<admin_contact email="" name="Yves Lussier and Carol Friedman are the principal investigators. The programmers are Jianrong Li, Lee Sam, and Tara Borlawsky" phone="" />

<comment type="desc:Version_Information" />

<comment type="desc:version_information" />

<comment type="desc:keywords">Phenotypic integration, computational phenotypes</comment>

<keyword type="license" value="n/a" />

<keyword type="release_date" value="Feb 2006" />

<keyword type="version" value="Version 2" />

<keyword ont_term_id="Natural_Language_Processing" ont_url="http://bioontology.org/ontologies/BiomedicalResourceOntology.owl" ontology="BRO" type="data_type" value="Natural_Language_Processing" />

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