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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   

•   Source: SciCrunch Registry

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   

•   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.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://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://purl.bioontology.org/ontology/PHYLONT

Ontology for Phylogenetic Analysis

Proper citation: Phylogenetic Ontology (RRID:SCR_000912) Copy   

•   Source: SciCrunch Registry

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

A taxonomy of Amphibia

Proper citation: Amphibian Taxonomy Ontology (RRID:SCR_000906) Copy   

•   Source: SciCrunch Registry

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

A comprehensive lexicon - a unified language of anatomic pathology terms - for standardized indexing and retrieval of anatomic pathology information resources.

Proper citation: Anatomic Pathology Lexicon (RRID:SCR_000907) Copy   

•   Source: SciCrunch Registry

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

Ontology that encompasses all knowledge about HIV

Proper citation: HIV ontology (RRID:SCR_000908) 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

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

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://purl.bioontology.org/ontology/BOF

An ontology of biodiversity of INPA

Proper citation: Biodiversity Ontology (RRID:SCR_010204) Copy   

•   Source: SciCrunch Registry

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

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

Proper citation: Gene Expression Ontology (RRID:SCR_010326) Copy   

•   Source: SciCrunch Registry

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

A top-level ontology integrating objects and processes.

Proper citation: General Formal Ontology (RRID:SCR_010328) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/GFO-BIO

A biological core ontology built on the General Formal Ontology.

Proper citation: General Formal Ontology for Biology (RRID:SCR_010329) Copy   

•   Source: SciCrunch Registry

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

Ontology that characterizes the state of current thought in cognitive science. It defines a set of mental concepts along with a set of mental tasks, and the measurement relations between those classes.

Proper citation: Cognitive Atlas Ontology (RRID:SCR_010295) Copy   

•   Source: SciCrunch Registry

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

A coding system for reporting adverse events that occur in the course of cancer therapy. It was derived from the Common Toxicity Criteria (CTC) v2.0 and is maintained by the Cancer Therapy Evaluation Program (CTEP) at the National Cancer Institution (NCI).

Proper citation: Common Terminology Criteria for Adverse Events (RRID:SCR_010296) Copy   

•   Source: SciCrunch Registry