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https://github.com/obophenotype/porifera-ontology

An ontology covering the anatomy of Porifera (sponges).

Proper citation: Porifera Ontology (RRID:SCR_000134) Copy   

•   Source: SciCrunch Registry

http://bioportal.bioontology.org/annotator

A Web service that annotates textual metadata (e.g. journal abstract) with relevant ontology concepts. NCBO uses this Web service to annotate resources in the NCBO Resource Index. They also provide this Web service as a stand-alone service for users. This Web service can be accessed through BioPortal or used directly in your software. Currently, the annotation workflow is based on syntactic concept recognition (using concept names and synonyms) and on a set of semantic expansion algorithms that leverage the semantics in ontologies (e.g., is_a relations). Their service methodology leverages ontologies to create annotations of raw text and returns them using semantic web standards.

Proper citation: NCBO Annotator (RRID:SCR_005329) Copy   

•   Source: SciCrunch Registry

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/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/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/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://purl.bioontology.org/ontology/JERM

An ontology to describe the entities and relationships in the SEEK database, a Systems Biology environment for the sharing and exchange of data and models. The SysMO-SEEK database contains the work of the SysMO consortium (Systems Biology of Micro-Organisms) https://seek.sysmo-db.org/

Proper citation: SysMO JERM Ontology of Systems Biology for Micro-Organisms (RRID:SCR_004569) Copy   

•   Source: SciCrunch Registry

http://www.proconsortium.org/pro/

An ontological representation of protein-related entities by explicitly defining them and showing the relationships between them. Each PRO term represents a distinct class of entities (including specific modified forms, orthologous isoforms, and protein complexes) ranging from the taxon-neutral to the taxon-specific. The ontology has a meta-structure encompassing three areas: proteins based on evolutionary relatedness (ProEvo); protein forms produced from a given gene locus (ProForm); and protein-containing complexes (ProComp). NOTICE: The PRO ID format has changed from PRO: to PR: (e.g. PRO:000000563 is now PR:000000563).

Proper citation: PR (RRID:SCR_004964) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GRO-CPD

A structured controlled vocabulary for describing cereal plant development and growth stages. Please note that this ontology has now been superseded by the Plant Ontology.

Proper citation: Cereal Plant Development Ontology (RRID:SCR_005095) Copy   

•   Source: SciCrunch Registry

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

An application ontology devoted to the standardized recording of phenotypic data related to hemorrhagic disorders.

Proper citation: Bleeding History Phenotype Ontology (RRID:SCR_001165) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ICD11-BODYSYSTEM

Ontology of a set of body-system terms used in the ICD (International Classification of Diseases) 11 revision

Proper citation: Body System Terms from ICD11 (RRID:SCR_001252) Copy   

•   Source: SciCrunch Registry

https://wiki.phenoscape.org/wiki/Teleost_Anatomy_Ontology

A multi-species anatomy ontology for teleost fishes. It was originally seeded from ZFA, but covers terms relevant to other taxa. The TAO uses terms from the Common Anatomy Reference Ontology (CARO) as a template for its upper level nodes, and the Vertebrate Skeletal Anatomy Ontology (VSAO) for general skeletal anatomy classes. Growth of the TAO is enabled by contributions from data curators and the ichthyological community. The TAO can be browsed by using the NCBO BioPortal and data annotated using TAO terms can be queried using the Phenoscape Knowedgebase.

Proper citation: Teleost Anatomy Ontology (RRID:SCR_001610) 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://bioassayontology.org/

Ontology to describe and categorize chemical biology and drug screening assays and their results including high-throughput screening (HTS) data for the purpose of categorizing assays and data analysis. BAO is an extensible, knowledge-based, highly expressive (currently SHOIQ(D)) description of biological assays making use of descriptive logic based features of the Web Ontology Language (OWL). BAO currently has over 700 classes and also makes use of several other ontologies. It describes several concepts related to biological screening, including Perturbagen, Format, Meta Target, Design, Detection Technology, and Endpoint. Perturbagens are perturbing agents that are screened in an assay; they are mostly small molecules. Assay Meta Target describes what is known about the biological system and / or its components interrogated in the assay (and influenced by the Perturbagen). Meta target can be directly described as a molecular entity (e.g. a purified protein or a protein complex), or indirectly by a biological process or event (e.g. phosphorylation). Format describes the biological or chemical features common to each test condition in the assay and includes biochemical, cell-based, organism-based, and variations thereof. The assay Design describes the assay methodology and implementation of how the perturbation of the biological system is translated into a detectable signal. Detection Technology relates to the physical method and technical details to detect and record a signal. Endpoints are the final HTS results as they are usually published (such as IC50, percent inhibition, etc). BAO has been designed to accommodate multiplexed assays. All main BAO components include multiple levels of sub-categories and specification classes, which are linked via object property relationships forming an expressive knowledge-based representation.

Proper citation: Bioassay Ontology (RRID:SCR_002638) Copy   

•   Source: SciCrunch Registry

http://www.geneontology.org/

Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.

Proper citation: Gene Ontology (RRID:SCR_002811) Copy   

•   Source: SciCrunch Registry

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

Ontology for representing events, time, and their relationships.

Proper citation: Time Event Ontology (RRID:SCR_000310) Copy   

•   Source: SciCrunch Registry

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

An ontology for standardized, systematic description of effects, consequences and mechanisms of variations.

Proper citation: Variation Ontology (RRID:SCR_000311) Copy   

•   Source: SciCrunch Registry