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http://purl.bioontology.org/ontology/GALEN

A translation of the full Galen ontology (from the OpenGALEN project) into the OWL description logic.

Proper citation: Galen Ontology (RRID:SCR_010325) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GO-EXT

An extension of the Gene Ontology.

Proper citation: Gene Ontology Extension (RRID:SCR_010327) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GENE-CDS

Ontology to unify several functionalities in a single resource, being: * A knowledge base for clinical pharmacogenomics/pharmacogenetics that can be used for question-answering (e.g., which SNPs are associated with this drug?) * A rule base for clinical decision support (e.g., inferring that a patient with a specific set of SNPs requires a lowered dose of warfarin and generating a CDS message that can be viewed by clinicians) * A tool for checking data consistency (e.g., highlighting which allele definitions in PharmGKB are overlapping, or which clinical decision support rules are matching the same group of patients)

Proper citation: Genomic Clinical Decision Support Ontology (RRID:SCR_010331) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CO

Ontology that includes crop-specific trait ontologies for several economically important plants like rice, wheat, maize, potato, musa, chickpea and sorghum along with other important domains for crop research such as germplasm, passport, trait measurement scales, experimental design factors etc.

Proper citation: Crop Ontology (RRID:SCR_010299) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GEOSPECIES

Ontology to help integrate species concepts with species occurrences, gene sequences, images, references and geographical information. See also Taxonconcept.org

Proper citation: GeoSpecies Ontology (RRID:SCR_010332) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/AMINO-ACID

An ontology of amino acids and their properties. Inferred version.

Proper citation: Amino Acid Ontology (RRID:SCR_010290) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/HLTHINDCTRS

Ontology for standardized health outcome and health determinant indicators as maintained by the CDC National Center for Health Statistics.

Proper citation: Health Indicator Ontology (RRID:SCR_010335) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/HL7

Ontology for the data types used in the creation of HL7 (Health Level Seven International) V3 specifications. This version is the first update to Normative RIM, Release 3. It is based on changes approved in Harmonization in November 2010. This release of the RIM is bound to HL7 Abstract Data Types Release 2. https://www.hl7.org/implement/standards/product_brief.cfm?product_id=264

Proper citation: Health Level Seven Reference Implementation Model Version 3 (RRID:SCR_010336) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/HINO

An Interaction Network Ontology (INO) extension for the domain of human interaction networks. It has currently incoporated Reactome reactions and pathways. Like INO, HINO aligns with BFO. HINO is developed by following the OBO Foundry principles.

Proper citation: Human Interaction Network Ontology (RRID:SCR_010339) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IMGT-ONTOLOGY

Ontology for immunogenetics and immunoinformatics. Provides semantic specification of terms to be used in immunogenetics and immunoinformatics and manages related knowledge, thus allowing standardization for immunogenetics data from genome, proteome, genetics, two-dimensional (2D) and three-dimensional (3D) structures. Manages the knowledge through diverse facets relying on seven axioms, IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, LOCALIZATION, ORIENTATION and OBTENTION. These axioms postulate that any object, any process and any relation can be identified, classified, described, numbered, localized and orientated, and the way it is obtained can be characterized. The axioms constitute the Formal IMGT-ONTOLOGY, also designated as IMGT-Kaleidoscope. As the same axioms can be used to generate concepts for multi-scale level approaches, the Formal IMGT-ONTOLOGY represents a paradigm for system biology ontologies, which need to identify, to classify, to describe, to number, to localize and to orientate objects, processes and relations at the molecule, cell, tissue, organ, organism or population levels. IMGT, the international ImMunoGeneTics information system, has been built on IMGT-ONTOLOGY. The version 1.0.2 of IMGT-ONTOLOGY includes the concepts of IDENTIFICATION and the concepts of CLASSIFICATION.

Proper citation: IMGT-ONTOLOGY (RRID:SCR_010342) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IDQA

Ontology for Image and Data Quality Assessment for scientific data management.

Proper citation: Image and Data Quality Assessment Ontology (RRID:SCR_010343) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/SYMP

Ontology designed around the guiding concept of a symptom being: A perceived change in function, sensation or appearance reported by a patient indicative of a disease. Understanding the close relationship of Signs and Symptoms, where Signs are the objective observation of an illness, the Symptom Ontology will work to broaden it''s scope to capture and document in a more robust manor these two sets of terms. Understanding that at times, the same term may be both a Sign and a Symptom

Proper citation: Symptom Ontology (RRID:SCR_010388) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/AURA

Ontology of the AURA + Inquire project at SRI International, Menlo Park.

Proper citation: KB Bio 101 (RRID:SCR_010268) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/CPT

Ontology of current procedural terminology.

Proper citation: Current Procedural Terminology (RRID:SCR_010301) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ONL-DP

Ontology that is a module of the OntoNeuroLOG ontology, that covers the domain of Datasets and the processing of datasets developed in the context of the NeuroLOG project, a french project aiming at integrating distributed heterogeous resources in neuroimaging. It includes a detailed taxonomy of datasets in the area of neuroimaging (and especially MR imaging) as well as a taxonomy of medical image processing.

Proper citation: Dataset processing (RRID:SCR_010303) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/OBCS

A biomedical ontology in the domain of biological and clinical statistics that is primarily targeted for statistical representation in the fields in biological, biomedical, and clinical domains. It uses the Basic Formal Ontology (BFO) as the upper level ontology. OBCS imports all biostatistics related terms in the Ontology for Biomedical Investigations (OBI) including all logical axioms.

Proper citation: Ontology of Biological and Clinical Statistics (RRID:SCR_010391) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/OCRE

Ontology to support systematic description of, and interoperable queries on, human studies and study elements.

Proper citation: Ontology of Clinical Research (RRID:SCR_010392) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/AI-RHEUM

Ontology used for the diagnosis of rheumatologic diseases. AI/RHEUM contains findings, such as clinical signs, symptoms, laboratory test results, radiologic observations, tissue biopsy results, and intermediate diagnosis hypotheses. Findings and hypotheses, which include definitions, are used to reach diagnostic conclusions with definite, probable, or possible certainty. AI/RHEUM is used by clinicians and informatics researchers.

Proper citation: Artificial Intelligence Rheumatology Consultant System Ontology (RRID:SCR_010274) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/LSM

An ontology of CD markers for lymphocyte classification in the cell ontology, and other categories of surface and secreted proteins useful for discriminating between lymphocyte subsets by flow cytometry, ELISPOT, ELISA and other assays typically used for phenotypic identification of individual lymphocytes or lymphocyte populations have been included.

Proper citation: Leukocyte Surface Marker Ontology (RRID:SCR_010275) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/IFAR

An application ontology devoted to the standardized recording of data related to Fanconi Anemia (FA). This ontology was created using an OWL file provided by Dr. Ada Hamish (and Francois Schiettecatte) at the Centers for Mendelian Genetics, with their permission. Their original ontology can be found at: http://phenodb.net/help/features. Modifications were made using HPO, OMIM, NCI, and SNOMED. Novel classes pertaining to FA were added and defined as appropriate.

Proper citation: Fanconi Anemia Ontology (RRID:SCR_010319) Copy   

•   Source: SciCrunch Registry