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http://hymao.org

A structured controlled vocabulary of the anatomy of the Hymenoptera (bees, wasps, sawflies and ants)

Proper citation: Hymenoptera Anatomy Ontology (RRID:SCR_003340) Copy   

•   Source: SciCrunch Registry

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

Ontology for cell types from NIFSTD

Proper citation: NIF Cell Ontology (RRID:SCR_003977) Copy   

•   Source: SciCrunch Registry

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

A structured controlled vocabulary for the annotation of mass spectrometry experiments.

Proper citation: Mass Spectrometry Ontology (RRID:SCR_003579) Copy   

•   Source: SciCrunch Registry

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

A reference ontology that models the life cycle stage details of various parasites, including Trypanosoma sp., Leishmania major, and Plasmodium sp., etc. In addition to life cycle stages, the ontology also models necessary contextual details, such as host information, vector information, and anatomical location. OPL is based on the Basic Formal Ontology (BFO) and follows the rules set by the OBO Foundry consortium.

Proper citation: Ontology for Parasite LifeCycle (RRID:SCR_003427) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/ontology-for-genetic-interval/

An ontology that formalized the genomic element by defining an upper class genetic interval using BFO as its framework. The definition of genetic interval is the spatial continuous physical entity which contains ordered genomic sets (DNA, RNA, Allele, Marker,etc.) between and including two points (Nucleic_Acid_Base_Residue) on a chromosome or RNA molecule which must have a liner primary sequence structure.

Proper citation: Ontology for Genetic Interval (RRID:SCR_003423) Copy   

•   Source: SciCrunch Registry

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

Ontology that provides a reference for describing an exercise in terms of functional movements, engaged musculoskeletal system parts, related equipment or monitoring devices, intended health outcomes, as well as target ailments for which the exercise might be employed as a treatment or preventative measure.

Proper citation: Ontology of Physical Exercises (RRID:SCR_003836) Copy   

•   Source: SciCrunch Registry

http://www.rightfield.org.uk/

An open-source tool for adding ontology term selection to Excel spreadsheets. It is used by a "Template Creator" to create semantically aware Excel spreadsheet templates. The Excel templates are then reused by Scientists to collect and annotate their data; without any need to understand, or even be aware of, RightField or the ontologies used. For each annotation field, RightField can specify a range of allowed terms from a chosen ontology (subclasses, individuals or combinations). The resulting spreadsheet presents these terms to the users as a simple drop-down list. This reduces the adoption barrier for using community ontologies as the annotation is made by the scientist that generated the data rather than a third party, and the annotation is collected at the time of data collection. RightField is a standalone Java application which uses Apache-POI for interacting with Microsoft documents. It enables users to import Excel spreadsheets, or generate new ones from scratch. Ontologies can either be imported from their local file systems, or from the BioPortal ontology repository. Individual cells, or whole columns or rows can be marked with the required ranges of ontology terms and an individual spreadsheet can be annotated with terms from multiple ontologies.

Proper citation: RightField (RRID:SCR_002649) 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

https://www.ebi.ac.uk/chebi/beta/

Collection of chemical compounds and other small molecular entities that incorporates an ontological classification of chemical compounds of biological relevance, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. The molecular entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms.

Proper citation: CHEBI (RRID:SCR_002088) Copy   

•   Source: SciCrunch Registry

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

A vocabulary that is able to describe and semantically interconnect the different paradigms of the cancer chemoprevention domain.

Proper citation: Cancer Chemoprevention Ontology (RRID:SCR_006966) Copy   

•   Source: SciCrunch Registry

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

Ontology that describes multi-cell computational models. In particular to describe both the existential behaviors of cells (spatiality, growth, movement, adhesion, death, ...) and computational models of those behaviors.

Proper citation: Cell Behavior Ontology (RRID:SCR_007055) Copy   

•   Source: SciCrunch Registry

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

Ontology designed for supporting the COG enrichment study by using Fisher''s exact test

Proper citation: Clusters of Orthologous Groups Analysis Ontology (RRID:SCR_007232) Copy   

•   Source: SciCrunch Registry

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

Ontology that represents CTX phenotypes, genetic variants, and bidirectional relationships between them though a patient model. The CTX ontology was built reusing the Human Phenotype Ontology (HPO) and the Snomed ct ontologies. A set of temporal clinical manifestations are semantically annotated with a domain phenotype ontology and registered with a time-stamped value.

Proper citation: Cerebrotendinous Xanthomatosis Ontology (RRID:SCR_007067) Copy   

•   Source: SciCrunch Registry

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

A small ontology for anatomical spatial references, such as dorsal, ventral, axis, and so forth.

Proper citation: Spatial Ontology (RRID:SCR_007860) Copy   

•   Source: SciCrunch Registry

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

Ontology of human dermatologic disease

Proper citation: Human Dermatological Disease Ontology (RRID:SCR_007648) Copy   

•   Source: SciCrunch Registry

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

Ontology for host pathogen interactions in farmed animals

Proper citation: Host Pathogen Interactions Ontology (RRID:SCR_007647) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/eagle-i/

Ontology that models research resources such as instruments, protocols, reagents, animal models and biospecimens. It has been developed in the context of the eagle-i project (http://eagle-i.net/) and consists of over 3451 classes of which over 1200 were created within the ERO namespace, while the rest come from existent ontologies such as the Ontology for Biomedical Investigation (OBI), the uber-anatomy ontology (Uberon), VIVO, the Ontology for Clinical Research (OCRe), the Sequence Ontology (SO), the Software Ontology (SWO) and we include terms from the NCBI Taxonomy as well. The main ontology can be browsed in OntoBee. All purls resolve to OntoBee.

Proper citation: eagle-i research resource ontology (RRID:SCR_008784) 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

https://genenames.org

Only worldwide authority that provides standardized nomenclature, i.e. gene names and symbols (short form abbreviations), for all known human genes, and stores all approved symbols in the HGNC database. Approved human gene nomenclature. Database of gene symbols and names. Manually curated genes into groups based on shared characteristics such as homology, function or phenotype. Data for protein-coding genes, pseudogenes and non-coding RNAs.

Proper citation: HGNC (RRID:SCR_002827) Copy   

•   Source: SciCrunch Registry