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

A web ontology for the semantic representation of the computer assisted brain trauma rehabilitation domain. This is a novel and emerging domain, since it employs the use of robotic devices, adaptation software and machine learning to facilitate interactive, adaptive and personalized rehabilitation care, patient monitoring and assisted living.

Proper citation: Computer Assisted Brain Injury Rehabilitation Ontology (RRID:SCR_005288) Copy   

•   Source: SciCrunch Registry

http://bmir.stanford.edu/

Mark Musen''s laboratory studies components for building knowledge-based systems, controlled terminologies and ontologies, and technology for the Semantic Web. For more than two decades, Musen''s group has worked to elucidate reusable building blocks of intelligent systems, and to develop scalable computational architectures for systems with significant applications in biomedicine. Informatics is the study of information: its structure, its communication, and its use. As society becomes increasingly information intensive, the need to understand, create, and apply new methods for modeling, managing, and acquiring information has never been greater especially in biomedicine. BMIR is home to world class scientists and trainees developing cutting-edge ways to acquire, represent, process, and manage knowledge and data related to health, health care, and the biomedical sciences. Our faculty, students, and staff are committed to ensuring the biomedical community is properly equipped for the information age, and believe our efforts will provide the structure for the burgeoning revolution of health care and the biomedical sciences.

Proper citation: Stanford Center for Biomedical Informatics Research (RRID:SCR_005698) Copy   

•   Source: SciCrunch Registry

http://www.clo-ontology.org/

A community-driven ontology that is developed to standardize and integrate cell line information and support computer-assisted reasoning. Its focus is on permanent cell lines from culture collections. Upper ontology structures that frame the skeleton of CLO include Basic Formal Ontology and Relation Ontology. Cell lines contained in CLO are associated with terms from other ontologies such as Cell Type Ontology, NCBI Taxonomy, and Ontology for Biomedical Investigation. A common design pattern for the cell line is used to model cell lines and their attributes, the Jurkat cell line provides ane xample. Currently CLO contains over 36,000 cell line entries obtained from ATCC, HyperCLDB, Coriell, and bymanual curation. The cell lines are derived from 194 cell types, 656 anatomical entries, and 217 organisms. The OWL-based CLO is machine-readable and can be used in various applications. The CLO development has become a community effort with international collaborations. The development consortium includes experts from all over the world: the USA, Europe, and Japan.

Proper citation: Cell Line Ontology (RRID:SCR_005840) Copy   

•   Source: SciCrunch Registry

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

Ontology specifically for Randomized Controlled Trials in order to facilitate the production of systematic reviews and metaanalysis.

Proper citation: Randomized Controlled Trials Ontology (RRID:SCR_005992) Copy   

•   Source: SciCrunch Registry

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

Ontology of clinical terms Version 3 (CTV3) (Read Codes) (Q199): National Health Service National Coding and Classification Centre

Proper citation: Read Codes Clinical Terms Version 3 (RRID:SCR_006055) Copy   

•   Source: SciCrunch Registry

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

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

Proper citation: Regulation of Transcription Ontology (RRID:SCR_006238) Copy   

•   Source: SciCrunch Registry

http://obi-ontology.org/

An ontology for the description of biological and clinical investigations built with international, collaborative effort. The ontology represents the design of an investigation, the protocols and instrumentation used, the material used, the data generated and the type analysis performed on it. This includes a set of universal terms that are applicable across various biological and technological domains, and domain-specific terms relevant only to a given domain. Currently OBI is being built under the Basic Formal Ontology (BFO). This project was formerly titled the Functional Genomics Investigation Ontology (FuGO) project.

Proper citation: Ontology for Biomedical Investigations (RRID:SCR_006266) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/

Private, non profit university in Stanford, California, USA for research and undergraduate and graduate studies. Known for its academic strength, wealth, proximity to Silicon Valley, and ranking as one of the world's top universities. Particularly noted for its entrepreneurship and is one of the most successful universities in attracting funding for start-ups.

Proper citation: Stanford University; Stanford; California (RRID:SCR_011538) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FB-SP

The taxonomy of the family Drosophilidae (largely after Baechli) and of other taxa referred to in FlyBase.

Proper citation: Fly Taxonomy (RRID:SCR_003317) Copy   

•   Source: SciCrunch Registry

http://www.nlm.nih.gov/mesh

A controlled vocabulary thesaurus that consists of sets of terms naming descriptors in a hierarchical structure that permits searching at various levels of specificity. MeSH, in machine-readable form, is provided at no charge via electronic means. MeSH descriptors are arranged in both an alphabetic and a hierarchical structure. At the most general level of the hierarchical structure are very broad headings such as Anatomy or Mental Disorders. More specific headings are found at more narrow levels of the twelve-level hierarchy, such as Ankle and Conduct Disorder. There are 27,149 descriptors in 2014 MeSH. There are also over 218,000 entry terms that assist in finding the most appropriate MeSH Heading, for example, Vitamin C is an entry term to Ascorbic Acid. In addition to these headings, there are more than 219,000 headings called Supplementary Concept Records (formerly Supplementary Chemical Records) within a separate thesaurus. The MeSH thesaurus is used by NLM for indexing articles from 5,400 of the world''''s leading biomedical journals for the MEDLINE/PubMED database. It is also used for the NLM-produced database that includes cataloging of books, documents, and audiovisuals acquired by the Library. Each bibliographic reference is associated with a set of MeSH terms that describe the content of the item. Similarly, search queries use MeSH vocabulary to find items on a desired topic.

Proper citation: MeSH (RRID:SCR_004750) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/WHO-ART

Ontology of the WHO adverse reaction terminology, 1997.

Proper citation: WHO Adverse Reaction Terminology (RRID:SCR_010447) Copy   

•   Source: SciCrunch Registry

https://blog.phenoscape.org/2008/05/14/the-teleost-taxonomy-ontology/

An ontology of taxonomic terms (names of taxonomic groups) used in the systematics of fish, including non-teleost groups such as Chondrichthys (sharks and rays), Sarcopterygii (lungfish and coelacanths), lampreys, and hagfish. It contains (as of August 2010) over 38,500 names, and over 44,000 taxonomic synonyms. A majority of the taxonomic names and synonyms were made available from the Catalog of Fishes. In July 2010 they added nearly 15,000 common names provided by Fishbase. Additional names and synonyms are added as a result of their curation activities. The ontology is being used to facilitate annotation of phenotypes, particularly for taxa that are not covered by NCBI because no submissions of molecular data have been made. Taxonomy ontologies can also be valuable in annotating legacy data, where authors make phenotype or ecological assertions (e.g., host-parasite associations) that refer to groups that are reorganized or no longer recognized. The taxonomy ontology serves as the source of taxa for their project's use for identifying evolutionary changes that match the phenotype of a zebrafish mutant.

Proper citation: Teleost Taxonomy Ontology (RRID:SCR_001611) Copy   

•   Source: SciCrunch Registry

http://cogpo.org

Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.

Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy   

•   Source: SciCrunch Registry

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

Ontology of clinical trial terminology.

Proper citation: Epoch Clinical Trial Ontology (RRID:SCR_000366) Copy   

•   Source: SciCrunch Registry

https://github.com/information-artifact-ontology/IAO

An ontology of information entities, originally driven by work by the OBI digital entity and realizable information entity branch. Please note: The ontology metrics displayed by BioPortal do not distinguish IAO-developed terms from terms imported from other ontologies.

Proper citation: Information Artifact Ontology (RRID:SCR_000477) Copy   

•   Source: SciCrunch Registry

http://aclame.ulb.ac.be/Classification/mego.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Gene Ontology dedicated to the functions of mobile genetic elements. The terms defined are used to annotate phage and plasmid protein families in ACLAME. Note: The phage ontology PhiGO has now been incorporated in MeGO and can thus be accessed in MeGO version 1.0 and up.

Proper citation: MeGO (RRID:SCR_000110) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. An anatomy ontology covering the vertebrate skeletal system that integrates terms for skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system.

Proper citation: Vertebrate Skeletal Anatomy Ontology (RRID:SCR_000313) Copy   

•   Source: SciCrunch Registry

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

Ontology for Inventories of Clinical Data Research Networks, Patient-Powered Research Networks, and Patient Registries

Proper citation: Research Network and Patient Registry Inventory Ontology (RRID:SCR_000308) Copy   

•   Source: SciCrunch Registry

http://environmentontology.org/

Community ontology for the concise, controlled description of environmental features and habitats. It provides a structured vocabulary that is designed to support the annotation of any organism or biological sample with environment descriptors. EnvO contains terms for biomes, environmental features, and environmental material.

Proper citation: EnvO (RRID:SCR_000182) Copy   

•   Source: SciCrunch Registry