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The Human Phenotype Ontology in 2017.

Köhler, Sebastian; Vasilevsky, Nicole A; Engelstad, Mark; Foster, Erin; McMurry, Julie; Aymé, Ségolène; Baynam, Gareth; Bello, Susan M; Boerkoel, Cornelius F; Boycott, Kym M; Brudno, Michael; Buske, Orion J; Chinnery, Patrick F; Cipriani, Valentina; Connell, Laureen E; Dawkins, Hugh J S; DeMare, Laura E; Devereau, Andrew D; de Vries, Bert B A; Firth, Helen V; Freson, Kathleen; Greene, Daniel; Hamosh, Ada; Helbig, Ingo; Hum, Courtney; Jähn, Johanna A; James, Roger; Krause, Roland; F Laulederkind, Stanley J; Lochmüller, Hanns; Lyon, Gholson J; Ogishima, Soichi; Olry, Annie; Ouwehand, Willem H; Pontikos, Nikolas; Rath, Ana; Schaefer, Franz; Scott, Richard H; Segal, Michael; Sergouniotis, Panagiotis I; Sever, Richard; Smith, Cynthia L; Straub, Volker; Thompson, Rachel; Turner, Catherine; Turro, Ernest; Veltman, Marijcke W M; Vulliamy, Tom; Yu, Jing; von Ziegenweidt, Julie.
Nucleic Acids Res; 45(D1): D865-D876, 2017 01 04.
Artigo em Inglês | MEDLINE | ID: mdl-27899602
Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.
Selo DaSilva