standards > terminology artifact > DOI:10.25504/FAIRsharing.kbtt7f


ready Human Phenotype Ontology

Abbreviation: HP


General Information
The Human Phenotype Ontology has been developed to provide a structured and controlled vocabulary for the phenotypic features encountered in human hereditary and other disease. The goal is to provide resource for the computational analysis of the human phenome, with a focus on monogenic diseases listed in the Online Mendelian Inheritance in Man (OMIM) and Orphanet databases, for which annotations are also provided.



How to cite this record FAIRsharing.org: HP; Human Phenotype Ontology; DOI: https://doi.org/10.25504/FAIRsharing.kbtt7f; Last edited: Feb. 22, 2018, 2:41 p.m.; Last accessed: Nov 19 2018 9:57 p.m.


This record is maintained by drseb  ORCID  and skoeher

Record updated: March 28, 2017, 12:58 p.m. by drseb.




Access / Retrieve Data


Publications

The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.

Kohler S,Doelken SC,Mungall CJ,Bauer S,Firth HV,Bailleul-Forestier I,Black GC,Brown DL,Brudno M,Campbell J,FitzPatrick DR,Eppig JT,Jackson AP,Freson K,Girdea M,Helbig I,Hurst JA,Jahn J,Jackson LG,Kelly AM,Ledbetter DH,Mansour S,Martin CL,Moss C,Mumford A,Ouwehand WH,Park SM,Riggs ER,Scott RH,Sisodiya S,Van Vooren S,Wapner RJ,Wilkie AO,Wright CF,Vulto-van Silfhout AT,de Leeuw N,de Vries BB,Washingthon NL,Smith CL,Westerfield M,Schofield P,Ruef BJ,Gkoutos GV,Haendel M,Smedley D,Lewis SE,Robinson PN
Nucleic Acids Res 2013

View Paper (PubMed) View Publication

The Human Phenotype Ontology in 2017.

Köhler S, Vasilevsky NA, Engelstad M, Foster E, McMurry J, Aymé S, Baynam G, Bello SM, Boerkoel CF, Boycott KM, Brudno M, Buske OJ, Chinnery PF, Cipriani V, Connell LE, Dawkins HJ, DeMare LE, Devereau AD, de Vries BB, Firth HV, Freson K, Greene D, Hamosh A, Helbig I, Hum C, Jähn JA, James R, Krause R, F Laulederkind SJ, Lochmüller H, Lyon GJ, Ogishima S, Olry A, Ouwehand WH, Pontikos N, Rath A, Schaefer F, Scott RH, Segal M, Sergouniotis PI, Sever R, Smith CL, Straub V, Thompson R, Turner C, Turro E, Veltman MW, Vulliamy T, Yu J, von Ziegenweidt J, Zankl A, Züchner S, Zemojtel T, Jacobsen JO, Groza T, Smedley D, Mungall CJ, Haendel M, Robinson PN.
Nucleic Acids Res. 2017

View Paper (PubMed) View Publication

HP Ontology Display

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Related Standards

Reporting Guidelines

No guidelines defined

Identifier Schemas

No identifier schema standards defined


Implementing Databases (10)
GWASdb
GWASdb comprises of collections of traits/diseases associated SNP (TASs) from current GWAS and their comprehensive functional annotations, as well as disease classifications

Mouse Genome Database - a Mouse Genome Informatics (MGI) Resource
MGI is the international database resource for the laboratory mouse, providing integrated genetic, genomic, and biological data to facilitate the study of human health and disease. Data includes gene characterization, nomenclature, mapping, gene homologies among mammals, sequence links, phenotypes, allelic variants and mutants, and strain data.

Orphanet
Orphanet is the reference resource for information on rare diseases and orphan drugs for all publics. Its aim is to contribute to the improvement of the diagnosis, care and treatment of patients with rare diseases. Orphanet maintains the Orphanet nomenclature, essential for interoperability, and the Orphanet Rare Disease Ontology (ORDO).

GWAS Central
Findings from genetic association studies.

ClinVar
ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. ClinVar thus facilitates access to and communication about the relationships asserted between human variation and observed health status, and the history of that interpretation. ClinVar processes submissions reporting variants found in patient samples, assertions made regarding their clinical significance, information about the submitter, and other supporting data. The alleles described in submissions are mapped to reference sequences, and reported according to the HGVS standard. ClinVar then presents the data for interactive users as well as those wishing to use ClinVar in daily workflows and other local applications. ClinVar works in collaboration with interested organizations to meet the needs of the medical genetics community as efficiently and effectively as possible.

Online Mendelian Inheritance in Man
OMIM is a comprehensive, authoritative compendium of human genes and genetic phenotypes that is freely available and updated daily. The full-text, referenced overviews in OMIM contain information on all known mendelian disorders and over 15,000 genes. OMIM focuses on the relationship between phenotype and genotype. It is updated daily, and the entries contain copious links to other genetics resources.

Target Central Resource Database
TCRD is the central resource behind the Illuminating the Druggable Genome Knowledge Management Center (IDG-KMC). TCRD contains information about human targets, with special emphasis on four families of targets that are central to the NIH IDG initiative: GPCRs, kinases, ion channels and nuclear receptors. Olfactory GPCRs (oGPCRs) are treated as a separate family. A key aim of the KMC is to classify the development/druggability level of targets. The official public portal for TCRD is Pharos (pharos.nih.gov). Based on modern web design principles the Pharos interface provides facile access to all data types collected by the KMC. Given the complexity of the data surrounding any target, efficient and intuitive visualization has been a high priority, to enable users to quickly navigate & summarize search results and rapidly identify patterns. A critical feature of the interface is the ability to perform flexible search and subsequent drill down of search results. Underlying the interface is a RESTful API that provides programmatic access to all KMC data, allowing for easy consumption in user applications.

Open Targets
Open Targets designed and developed an integration and visualization platform that provides evidence about the association of known and potential drug targets with diseases. The platform is designed to support identification and prioritization of biological targets for follow-up. Each drug target is linked to a disease using integrated genome-wide data from a broad range of data sources. The platform provides either a target-centric workflow to identify diseases that may be associated with a specific target, or a disease-centric workflow to identify targets that may be associated with a specific disease. Users can easily transition between these target- and disease-centric workflows.

MalaCards
The MalaCards human disease database (http://www. malacards.org/) is an integrated compendium of annotated diseases mined from 68 data sources. MalaCards has a web card for each of ∼20 000 disease entries, in six global categories. It portrays a broad array of annotation topics in 15 sections, including Summaries, Symptoms, Anatomical Context, Drugs, Genetic Tests, Variations and Publications. The Aliases and Classifications section reflects an algorithm for disease name integration across often-conflicting sources, providing effective annotation consolidation. A central feature is a balanced Genes section, with scores reflecting the strength of disease-gene associations. This is accompanied by other gene-related disease information such as pathways, mouse phenotypes and GO-terms, stemming from MalaCards’ affiliation with the GeneCards Suite of databases. MalaCards’ capacity to inter-link information from complementary sources, along with its elaborate search function, relational database infrastructure and convenient data dumps, allows it to tackle its rich disease annotation landscape, and facilitates systems analyses and genome sequence interpretation. MalaCards adopts a ‘flat’ disease-card approach, but each card is mapped to popular hierarchical ontologies (e.g. International Classification of Diseases, Human Phenotype Ontology and Unified Medical Language System) and also contains information about multi-level relations among diseases, thereby providing an optimal tool for disease representation and scrutiny.

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.

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Implementing Policies

This record is not implemented by any policy.


Credit

Record Maintainer

Funds

Maintains

Grant Number(s)

  • 602300 (European Community Seventh Framework Programme)

  • BMBF project number 0313911 (Federal Ministry of Education and Research (BMBF), Berlin, Germany)

  • DFG RO 2005/4-2 (The Deutsche Forschungsgemeinschaft)