Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

Search

Type in a keyword to search

On page 1 showing 1 ~ 20 out of 379 results
Snippet view Table view Download 379 Result(s)
Click the to add this resource to a Collection
  • RRID:SCR_006627

    This resource has 1+ mentions.

https://wiki.nci.nih.gov/display/LexEVS/LexGrid

LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: LexGrid (RRID:SCR_006627) Copy   


  • RRID:SCR_001976

    This resource has 1+ mentions.

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   


  • RRID:SCR_002649

    This resource has 1+ mentions.

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   


  • RRID:SCR_000473

    This resource has 1+ mentions.

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

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 23, 2014. Description not available.

Proper citation: Gazetteer (RRID:SCR_000473) Copy   


  • RRID:SCR_007326

http://fireball.drexelmed.edu/birnlex/OWLdocs/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on April 26, 2011. Lexicon that provides entities for data and database annotation for the BIRN project, covering anatomy, disease, data collection, project management and experimental design. These sources may include complex image databases, such as data from structural and functional magnetic resonance imaging (MRI) on human subjects involved in studies on Alzheimer''s disease or schizophrenia. The BIRNLex is a specialized vocabulary utilized by BIRN scientists in the context of their research, including common terms for neuroanatomy, molecular species, subject information, behavioral and cognitive processes, experimental practice and design, and the associated elements of primary data provenance required for large-scale data integration across disparate experimental studies.The BIRNLex offers well defined terms from several domains of importance to neuroimaging across scales.

Proper citation: BIRNLex (RRID:SCR_007326) Copy   


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

A controlled vocabulary of terms used in Computational Neurosciences to describe models of the nervous system. This first release of CNO is an alpha version and should be further aligned with other ontologies accessible on Bioportal and should be made compliant with the OBO foundry recommendations.

Proper citation: Computational Neuroscience Ontology (RRID:SCR_007289) Copy   


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

Ontology for Solanaceae crop phenotypes and traits, developed in collaboration with the research community, especially for breeder traits of agronomic importance.

Proper citation: Solanaceae Phenotype Ontology (RRID:SCR_007832) Copy   


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

A uniform core set of data elements (whose formal semantics are captured in OWL) for use in a Computer-Based Patient Record (CPR)

Proper citation: Computer-Based Patient Record Ontology (RRID:SCR_007540) Copy   


  • RRID:SCR_007847

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

Growth, trait and development ontology for soybean

Proper citation: Soy Ontology (RRID:SCR_007847) Copy   


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

Ontology for the healthcare common procedure coding system.

Proper citation: Healthcare Common Procedure Coding System (RRID:SCR_007598) Copy   


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

An evidence taxonomy for pharmacologic studies that, when combined with a set of inclusion criteria, enable drug experts to specify what their confidence in a drug mechanism assertion would be if it were supported by a specific set of evidence.

Proper citation: Drug Interaction Knowledge Base Ontology (RRID:SCR_007591) Copy   


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

An ontology that describes the Congenital Heart Defects data.

Proper citation: Congenital Heart Defects Ontology (RRID:SCR_007584) Copy   


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

Memorial Sloan-Kettering Cancer Center''s ontology of surgical secondary events (adverse events).

Proper citation: Surgical Secondary Events (RRID:SCR_007894) Copy   


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

A structured controlled vocabulary for the phenotypes of Ascomycete fungi.

Proper citation: Ascomycete Phenotype Ontology (RRID:SCR_003254) Copy   


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

An application ontology built for the Beta Cell Genomics database aiming to support database annotation, complicated semantic queries, and automated cell type classification. The ontology is developed using Basic Formal Ontology (BFO) as upper ontology, Ontology for Biomedical Investigations (OBI) as ontology framework and integrated subsets of multiple OBO Foundry (candidate) ontologies. Current the BCGO contains 2383 classes including terms referencing to 24 various OBO Foundry ontologies including CL, CLO, UBERON, GO, PRO, UO, etc.

Proper citation: Beta Cell Genomics Ontology (RRID:SCR_003259) Copy   


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

A structured controlled vocabulary of the anatomy of the slime-mould Dictyostelium discoideum.

Proper citation: Dictyostelium Discoideum Anatomy Ontology (RRID:SCR_003309) Copy   


http://code.google.com/p/bco/

Ontology developed as an application ontology as part of the Biocode Commons project whose goal is to support the interoperability of biodiversity data, including data on museum collections, environmental and metagenomic samples, and ecological surveys. It includes consideration of the distinctions between individuals, organisms, voucher specimens, lots, and samples the relations between these entities, and processes governing the creation and use of samples. Within scope as well are properties including collector, location, time, storage environment, containers, institution, and collection identifiers.

Proper citation: Biological Collections Ontology (RRID:SCR_003262) Copy   


http://www.bioontology.org/wiki/index.php/CARO:Main_Page

An ontology developed to facilitate interoperability between existing anatomy ontologies for different species, and to provide a template for building new anatomy ontologies.

Proper citation: Common Anatomy Reference Ontology (RRID:SCR_003296) Copy   


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   


  • RRID:SCR_003286

    This resource has 1+ mentions.

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   



Can't find your Tool?

We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.

Can't find the RRID you're searching for? X
  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within FDI Lab - SciCrunch.org that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

X