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http://purl.bioontology.org/ontology/CMO
An ontology designed to be used to standardize morphological and physiological measurement records generated from clinical and model organism research and health programs.
Proper citation: Clinical Measurement Ontology (RRID:SCR_003291) Copy
https://github.com/rsc-ontologies/rsc-cmo
An ontology that describes methods used to collect data in chemical experiments, such as mass spectrometry and electron microscopy; preparing and separating material for further analysis, such as sample ionization, chromatography, and electrophoresis; and synthesizing materials, such as epitaxy and continuous vapor deposition. It also describes the instruments used in these experiments, such as mass spectrometers and chromatography columns. It is intended to be complementary to the Ontology for Biomedical Investigations (OBI).
Proper citation: Chemical Methods Ontology (RRID:SCR_003286) Copy
http://purl.bioontology.org/ontology/FB-CV
A structured controlled vocabulary used for various aspects of annotation by FlyBase. This ontology is maintained by FlyBase for various aspects of annotation not covered, or not yet covered, by other OBO ontologies. If and when community ontologies are available for the domains here covered FlyBase will use them.
Proper citation: FlyBase Controlled Vocabulary (RRID:SCR_003318) Copy
http://purl.bioontology.org/ontology/FYPO
A formal ontology of phenotypes observed in fission yeast that is being developed to support the comprehensive and detailed representation of phenotypes in PomBase, the online fission yeast resource. Its scope is similar to that of the Ascomycete Phenotype Ontology (APO), but FYPO includes more detailed pre-composed terms as well as computable definitions.
Proper citation: Fission Yeast Phenotype Ontology (RRID:SCR_003315) Copy
http://code.google.com/p/popcomm-ontology/
An ontology that models material entities, qualities, and processes related to collections of interacting organisms such as populations and communities. It is taxon neutral, and can be used for any species, including humans. The classes in the PCO are useful for describing evolutionary processes, organismal interactions, and ecological experiments. Practical applications of the PCO include community health care, plant pathology, behavioral studies, sociology, and ecology. The PCO is compliant with the Basic Formal Ontology (BFO) and is designed to be compatible with other OBO Foundry ontologies, such as the Gene Ontology (GO), which covers biological processes, and the Phenotypic Quality Ontology (PATO).
Proper citation: Population and Community Ontology (RRID:SCR_003462) Copy
http://archive.gramene.org/plant_ontology/ontology_browse.html#eo
A structured controlled vocabulary for the representation of plant environmental conditions.
Proper citation: Plant Environmental Conditions (RRID:SCR_003460) Copy
http://code.google.com/p/pharmgkb-owl/
An OWL representation of the data in PharmGKB, Comparative Toxicogenomics Database (CTD) and DrugBank and linked to related ontologies: ChEBI ontology, the Human Disease Ontology (DO), the Anatomical Therapeutic Chemical Classification System (ATC) and the Medical Subject Headings Thesaurus (MESH). The combined knowledge base can be exploited using the ELK reasoner.
Proper citation: PharmGKB Ontology (RRID:SCR_003529) Copy
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
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
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
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
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
Biomedical ontology in the domain of adverse events that aims to standardize adverse event annotation, integrate various adverse event data, and support computer-assisted reasoning. AEO is a community-based ontology. Its development follows the OBO Foundry principles.
Proper citation: Ontology of Adverse Events (RRID:SCR_003428) Copy
http://rgd.mcw.edu/tools/ontology/ont_search.cgi
Ontology that defines hierarchical display of different rat strains as derived from parental strains. Ontology Browser allows to retrieve all genes, QTLs, strains and homologs annotated to particular term. Covers all types of biological pathways including altered and disease pathways, and to capture relationships between them within hierarchical structure. Five nodes of ontology include classic metabolic, regulatory, signaling, drug and disease pathways. Ontology allows for standardized annotation of rat. Serves as vehicle to connect between genes and ontology reports, between reports and interactive pathway diagrams, between pathways that directly connect to one another within diagram or between pathways that in some fashion are globally related in pathway suites and suite networks.
Proper citation: Rat Strain Ontology (RRID:SCR_003449) Copy
A biomedical ontology in the area of vaccine adverse events aimed to represent and analyze various vaccine-specific adverse events. OVAE is an extension of the Ontology of Adverse Events (OAE) and the Vaccine Ontology (VO).
Proper citation: Ontology of Vaccine Adverse Events (RRID:SCR_003442) Copy
http://code.google.com/p/omrse/
An ontology covering the domain of social entities that are related to health care, such as demographic information (social entities for recording gender (but not sex) and marital status, for example) and the roles of various individuals and organizations (patient, hospital, etc.)
Proper citation: Ontology of Medically Related Social Entities (RRID:SCR_003439) Copy
http://purl.bioontology.org/ontology/MEDDRA
Ontology of Medical Dictionary for Regulatory Activities Terminology (MedDRA)
Proper citation: Medical Dictionary for Regulatory Activities (RRID:SCR_003751) Copy
An application focused ontology modelling the experimental factors in ArrayExpress and Gene Expression Atlas. It has been developed to increase the richness of the annotations that are currently made in the ArrayExpress repository, to promote consistent annotation, to facilitate automatic annotation and to integrate external data. The ontology describes cross-product classes from reference ontologies in area such as disease, cell line, cell type and anatomy. The methodology employed in the development of EFO involves construction of mappings to multiple existing domain specific ontologies, such as the Disease Ontology and Cell Type Ontology. This is achieved using a combination of automated and manual curation steps and the use of a phonetic matching algorithm. The ontology is evaluated with use cases from the ArrayExpress repository and ArrayExpress Atlas. You may also browse the EFO in the NCBO Bioportal. Term submissions are welcome.
Proper citation: Experimental Factor Ontology (RRID:SCR_003574) Copy
http://code.google.com/p/adverse-event-reporting-ontology/
An ontology aimed at supporting clinicians at the time of data entry, increasing quality and accuracy of reported adverse events.
Proper citation: Adverse Event Reporting Ontology (RRID:SCR_003571) Copy
http://purl.bioontology.org/ontology/MDCDRG
Ontology of Medical Diagnostic Categories-Diagnosis Related Groups
Proper citation: Medical Diagnostic Categories - Diagnosis Related Groups (RRID:SCR_003725) Copy
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