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PhenoGO: an integrated resource for the multiscale mining of clinical and biological data

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: PhenoGO: an integrated resource for the multiscale mining of clinical and biological data
Συγγραφείς: Sam, Lee, Mendonça, Eneida, Li, Jianrong, Blake, Judith, Friedman, Carol, Lussier, Yves
Στοιχεία εκδότη: BioMed Central
Έτος έκδοσης: 2009
Συλλογή: Columbia University: Academic Commons
Θεματικοί όροι: Bioinformatics, Genetics--Data processing, Genetics—Research
Περιγραφή: The evolving complexity of genome-scale experiments has increasingly centralized the role of a highly computable, accurate, and comprehensive resource spanning multiple biological scales and viewpoints. To provide a resource to meet this need, we have significantly extended the PhenoGO database with gene-disease specific annotations and included an additional ten species. This a computationally-derived resource is primarily intended to provide phenotypic context (cell type, tissue, organ, and disease) for mining existing associations between gene products and GO terms specified in the Gene Ontology Databases Automated natural language processing (BioMedLEE) and computational ontology (PhenOS) methods were used to derive these relationships from the literature, expanding the database with information from ten additional species to include over 600,000 phenotypic contexts spanning eleven species from five GO annotation databases. A comprehensive evaluation evaluating the mappings (n = 300) found precision (positive predictive value) at 85%, and recall (sensitivity) at 76%. Phenotypes are encoded in general purpose ontologies such as Cell Ontology, the Unified Medical Language System, and in specialized ontologies such as the Mouse Anatomy and the Mammalian Phenotype Ontology. A web portal has also been developed, allowing for advanced filtering and querying of the database as well as download of the entire dataset http://www.phenogo.org.
Τύπος εγγράφου: article in journal/newspaper
Γλώσσα: English
Relation: https://doi.org/10.7916/D8XD1038
DOI: 10.7916/D8XD1038
Διαθεσιμότητα: https://doi.org/10.7916/D8XD1038
Αριθμός Καταχώρησης: edsbas.9497A572
Βάση Δεδομένων: BASE
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  Data: PhenoGO: an integrated resource for the multiscale mining of clinical and biological data
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  Data: <searchLink fieldCode="AR" term="%22Sam%2C+Lee%22">Sam, Lee</searchLink><br /><searchLink fieldCode="AR" term="%22Mendonça%2C+Eneida%22">Mendonça, Eneida</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Jianrong%22">Li, Jianrong</searchLink><br /><searchLink fieldCode="AR" term="%22Blake%2C+Judith%22">Blake, Judith</searchLink><br /><searchLink fieldCode="AR" term="%22Friedman%2C+Carol%22">Friedman, Carol</searchLink><br /><searchLink fieldCode="AR" term="%22Lussier%2C+Yves%22">Lussier, Yves</searchLink>
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  Data: 2009
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  Data: The evolving complexity of genome-scale experiments has increasingly centralized the role of a highly computable, accurate, and comprehensive resource spanning multiple biological scales and viewpoints. To provide a resource to meet this need, we have significantly extended the PhenoGO database with gene-disease specific annotations and included an additional ten species. This a computationally-derived resource is primarily intended to provide phenotypic context (cell type, tissue, organ, and disease) for mining existing associations between gene products and GO terms specified in the Gene Ontology Databases Automated natural language processing (BioMedLEE) and computational ontology (PhenOS) methods were used to derive these relationships from the literature, expanding the database with information from ten additional species to include over 600,000 phenotypic contexts spanning eleven species from five GO annotation databases. A comprehensive evaluation evaluating the mappings (n = 300) found precision (positive predictive value) at 85%, and recall (sensitivity) at 76%. Phenotypes are encoded in general purpose ontologies such as Cell Ontology, the Unified Medical Language System, and in specialized ontologies such as the Mouse Anatomy and the Mammalian Phenotype Ontology. A web portal has also been developed, allowing for advanced filtering and querying of the database as well as download of the entire dataset http://www.phenogo.org.
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