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http://sig.biostr.washington.edu/projects/fm/

A domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. It is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Its ontological framework can be applied and extended to all other species. The description of how the OWL version was generated is in Pushing the Envelope: Challenges in a Frame-Based Representation of Human Anatomy by N. F. Noy, J. L. Mejino, C. Rosse, M. A. Musen: http://bmir.stanford.edu/publications/view.php/pushing_the_envelope_challenges_in_a_frame_based_representation_of_human_anatomy The Foundational Model of Anatomy ontology has four interrelated components: # Anatomy taxonomy (At), # Anatomical Structural Abstraction (ASA), # Anatomical Transformation Abstraction (ATA), # Metaknowledge (Mk), The ontology contains approximately 75,000 classes and over 120,000 terms; over 2.1 million relationship instances from over 168 relationship types link the FMA's classes into a coherent symbolic model.

Proper citation: FMA (RRID:SCR_003379) Copy   

•   Source: SciCrunch Registry

http://omim.org

Online catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.

Proper citation: OMIM (RRID:SCR_006437) Copy   

•   Source: SciCrunch Registry

http://www.biopax.org/

Community standard for pathway data sharing. Standard language that aims to enable integration, exchange, visualization and analysis of biological pathway data. Supports data exchange between pathway data groups and thus reduces complexity of interchange between data formats by providing accepted standard format for pathway data. Open and collaborative effort by community of researchers, software developers, and institutions. BioPAX is defined in OWL DL and is represented in RDF/XML format.Uses W3C standard Web Ontology Language, OWL.

Proper citation: Biological Pathways Exchange (RRID:SCR_001681) Copy   

•   Source: SciCrunch Registry

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

An application ontology for the domain of gene expression regulation. The ontology integrates fragments of GO and MI with data from GOA, IntAct, UniProt, NCBI, KEGG and orthology relations.

Proper citation: Regulation of Gene Expression Ontolology (RRID:SCR_006124) Copy   

•   Source: SciCrunch Registry

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

Ontology for livestock reproductive traits and phenotypes

Proper citation: Reproductive Trait and Phenotype Ontology (RRID:SCR_006245) Copy   

•   Source: SciCrunch Registry

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

Ontology for the description of student health records. Student health records are created for entering college students in order to provide better health services will be formed. This file contains various sections such as history of disease, family history of disease, public examinations and ... .

Proper citation: Student Health Record Ontology (RRID:SCR_005854) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/behavior-ontology

An ontology consisting of two main components, an ontology of behavioral processes and an ontology of behavioral phenotypes. The behavioral process branch of NBO contains a classification of behavior processes complementing and extending the GO process ontology. The behavior phenotype branch of NBO consists of a classification of both normal and abnormal behavioral characteristics of organisms. The prime application of NBO is to provide the vocabulary that is required to integrate behavior observations within and across species. It is currently being applied by several model organism communities as well as in the description of human behavior-related disease phenotypes. The main ontology is available in both the OBO Flatfile Format and the Web Ontology Language (OWL).

Proper citation: Neurobehavior Ontology (RRID:SCR_006201) Copy   

•   Source: SciCrunch Registry

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

A structured controlled vocabulary of stage-specific anatomical structures of the human. It has been designed to mesh with the mouse anatomy and incorporates each Carnegie stage of development (CS1-20). The timed version of the human developmental anatomy ontology gives all the tissues present at each Carnegie Stage (CS) of human development (1-20) linked by a part-of rule. Each term is mentioned only once so that the embryo at each stage can be seen as the simple sum of its parts. Users should note that tissues that are symmetric (e.g. eyes, ears, limbs) are only mentioned once.

Proper citation: Human Developmental Anatomy Ontology timed version (RRID:SCR_010338) Copy   

•   Source: SciCrunch Registry

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

Ontology as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles.

Proper citation: Human Physiology Simulation Ontology (RRID:SCR_010340) Copy   

•   Source: SciCrunch Registry

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

Ontology of logical observation identifier names and codes (LOINC); Version 2.26; January 2, 2009

Proper citation: Logical Observation Identifier Names and Codes (RRID:SCR_010341) Copy   

•   Source: SciCrunch Registry

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

DICOM Controlled Terminology (PS3.16 2013 Annex D)

Proper citation: DICOM Controlled Terminology (RRID:SCR_010302) Copy   

•   Source: SciCrunch Registry

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

A computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct SR-MA (Systematic Review - Meta Analysis) for diagnostic studies, that will assist in standardized reporting of diagnostic articles. They also report high percentage of agreement among five observers as a result of the inter-observer agreement that they conducted among them to tag 13 articles using the diagnostic ontology. Moreover, they extend their existing repository CERR-N (Center of Excellence in Research Reporting in Neurosurgery) to include diagnostic studies.

Proper citation: Diagnostic Ontology (RRID:SCR_010307) Copy   

•   Source: SciCrunch Registry

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

A high level patient-centric ontology for the pharmaceutical industry. The ontology should enable silos in discovery research, hypothesis management, experimental studies, compounds, formulation, drug development, market size, competitive data, population data, etc. to be brought together. This would enable scientists to answer new questions, and to answer existing scientific questions more quickly. This will help pharmaceutical companies to model patient-centric information, which is essential for the tailoring of drugs, and for early detection of compounds that may have sub-optimal safety profiles. The ontology should link to existing publicly available domain ontologies.

Proper citation: Translational Medicine Ontology (RRID:SCR_010439) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/BP-METADATA

Ontology that represents the structure that BioPortal uses to represent all of its metadata (ontology details, mappings, notes, reviews, views)

Proper citation: BioPortal Metadata Ontology (RRID:SCR_010167) Copy   

•   Source: SciCrunch Registry

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

An ontology for animal life history and natural history characteristics suitable for populations and higher taxonomic entities.

Proper citation: Animal Natural History and Life History Ontology (RRID:SCR_010292) Copy   

•   Source: SciCrunch Registry

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

Ontology for coding, filing, and retrieving post-marketing adverse drug and biologic experience reports. It is organized in body system and pathophysiology hierarchies, as well as a separate fetal/neonatal category of less than 20 terms. COSTART has been superseded by the Medical Dictionary for Regulatory Activities (MedDRA) Terminology. For more information about MedDRA in the Metathesaurus, see the MedDRA source synopsis. COSTART was last updated in the Metathesaurus in 1999.

Proper citation: Coding Symbols for a Thesaurus of Adverse Reaction Terms (RRID:SCR_010294) Copy   

•   Source: SciCrunch Registry

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

Ontology that is an automatic translation of the NCBI taxonomy (a taxonomic classification of living organisms and associated artifacts) database into obo/owl.

Proper citation: NCBITaxon (RRID:SCR_000479) Copy   

•   Source: SciCrunch Registry

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

An ontology for courtship behavior of the spider Habronattus californicus. A demonstration of ontology construction as a general technique for coding ethograms and other descriptions of behavior into machine understandable forms.

Proper citation: Habronattus Courtship Ontology (RRID:SCR_010334) Copy   

•   Source: SciCrunch Registry

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

Ontology that facilitates representing the family health histories of persons related by biological and/or social family relationships (e.g. step, adoptive) who share genetic, behavioral, and/or environmental risk factors for disease. SWRL rules are included to compute 3 generations of biological relationships based on parentage and family history findings based on personal health findings.

Proper citation: Family Health History Ontology (RRID:SCR_010068) Copy   

•   Source: SciCrunch Registry

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

Ontology that is a schema for information brokering and knowledge management in the complex field of rare diseases. On the one hand, the Dispedia schema uses semantic technologies to describe patients affected by rare diseases, and on the other hand, to record expertise concerning these particular diseases in machine-processable form. In addition to the differentiated attribution of facts to the individual need for information, Dispedia enables information brokering which adjusts to the type of recipient, its character as well as its personal attitude. The schema was initially geared to an exemplified disease, Amyotrophe Lateralsclerose (ALS).

Proper citation: Dispedia Core Ontology (RRID:SCR_010309) Copy   

•   Source: SciCrunch Registry