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http://purl.bioontology.org/ontology/ICD10

Ontology of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). 10th rev. Geneva, a medical classification list by the World Health Organization (WHO).

Proper citation: International Classification of Diseases Version 10 (RRID:SCR_010349) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ICD10PCS

Ontology of the International Classification of Diseases Version 10, ICD-10-PCS (Procedure Coding System), 2009.

Proper citation: International Classification of Diseases Version 10 - Procedure Coding System (RRID:SCR_010351) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ONL-MR-DA

Ontology that is a module of the OntoNeuroLOG ontology, that covers the domain of Magnetic Resonance Imaging (MRI) dataset acquisition, i.e. MRI protocols, and MRI sequence parameters, developed in the context of the NeuroLOG project, a french project aiming at integrating distributed heterogeneous resources in neuroimaging. In particular, it includes a multi-axial classification of MR sequences.

Proper citation: MR dataset acquisition (RRID:SCR_010352) Copy   

•   Source: SciCrunch Registry

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

Ontology for organismal habitats (especially focused on microbes)

Proper citation: Metagenome and Microbes Environmental Ontology (RRID:SCR_010359) Copy   

•   Source: SciCrunch Registry

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

Controlled vocabularies for the MIxS (Minimal Information about any Sequence) family of metadata checklists. See http://gensc.org/gc_wiki/index.php/MIxS for details on the MIxS checklists.

Proper citation: Minimal Information about any Sequence Controlled Vocabularies (RRID:SCR_010363) Copy   

•   Source: SciCrunch Registry

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

Ontology that is a conceptual model for the domain of gene regulation. It covers processes that are linked to the regulation of gene expression as well as physical entities that are involved in these processes (such as genes and transcription factors) in terms of ontology classes and semantic relations between classes. GRO is intended to represent common knowledge about gene regulation in a formal way rather than representing extremely fine-grained classes as can be found in ontologies such as the Gene Ontology (GO) (created for data base annotation purposes) and various relevant databases. The main purpose of the ontology is to support NLP applications. It has a particular focus on the relations between processes and the molecules (participants) involved. The basic structure of the GRO is a direct acyclic graph (DAG) with ontology classes as nodes and is-a relations between classes as edges. The taxonomic backbone is further enriched by several semantic relation types (part-of, from-species, participates-in with the two sub-relations agent-of and patient-of).

Proper citation: Gene Regulation Ontology (RRID:SCR_010590) Copy   

•   Source: SciCrunch Registry

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

Ontology that provides an up-to-date knowledge base of experimentally verified glycan structures. Glycan (oligosaccharide or polysaccharide) structures are represented as trees of monosaccharide residues. Linkage to proteins and lipids is supported as well. Insertion of a new glycan is controlled by curation process that includes matching the new glycan against a canonical glyco-tree (a highly branched representation for a family of glycans).

Proper citation: Glycomics Ontology (RRID:SCR_010333) Copy   

•   Source: SciCrunch Registry

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

A domain ontology that provides a formal representation (OWL-DL) of genomic variations. Despite its name it is not limited to the representation of SNPs but it encompasses genomic variations in a broader meaning. SNP-Ontology is general enough to enable the representation of variations observed in genome of various species. Latest versions of SNP-Ontology include the representation of haplotype and of CNV. The unambiguous representation of genomic variations provided by SNP-Ontology enables to integrate heterogeneous data related to genomic variations. To achieve this goal SNP-Ontology enables (1) to represent one variation in accordance with various ways that exist for describing it, (2) to represent the equivalence between two distinct descriptions of one variation, and (3) to represent correspondence between a genomic variation and its outcome at the transcriptome and proteome levels.

Proper citation: Single-Nucleotide Polymorphism Ontology (RRID:SCR_010428) Copy   

•   Source: SciCrunch Registry

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

An Ontology describing Resources having different formats. This Ontology can be used to annotate and describe Terminological, Ontological Knowledge resources.

Proper citation: Terminological and Ontological Knowledge Resources Ontology (RRID:SCR_010432) Copy   

•   Source: SciCrunch Registry

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

Ontology terms useful for machine learning experiments. The terminology appearing in JMLA has been enriched with terms from MeSH and Emtree, the controlled vocabularies for MEDLINE and Embase, respectively. Synonyms include American and British variants and some inverted terms.

Proper citation: EDDA Study Design Terminology (RRID:SCR_010312) Copy   

•   Source: SciCrunch Registry

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

An OWL schema that expands upon the Tissue microarray (TMA) data exchange specification to assist in data sharing and integration.

Proper citation: Tissue Microarray Ontology (RRID:SCR_010434) Copy   

•   Source: SciCrunch Registry

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

Ontology that describes the field of Tissue Engineering for what concerns bone and cartilage tissues.

Proper citation: Bone and Cartilage Tissue Engineering Ontology (RRID:SCR_006595) Copy   

•   Source: SciCrunch Registry

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

Nomenclature for innovative activity of biology and anatomo-pathology performed especially in the Centres Hospitalo-Universitaires is usually called activity off nomenclature (BHN for nomenclature and PHN biology for the anatomo-pathology off nomenclature). This character of nomenclature means that health insurance has not yet incorporated these acts in the Nomenclature of acts of biology medical (NABM) or the General Nomenclature of professional acts (NGAP).

Proper citation: Biologie Hors Nomenclature (RRID:SCR_010249) Copy   

•   Source: SciCrunch Registry

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

Vocabulary that describes a process that is the means of how a pathogen is transmitted from one host, reservoir, or source to another host. This transmission may occur either directly or indirectly and may involve animate vectors or inanimate vehicles.

Proper citation: Pathogen Transmission Ontology (RRID:SCR_010404) Copy   

•   Source: SciCrunch Registry

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

A controlled vocabulary of growth and developmental stages in various plants. Note that this has been subsumed into the Plant Ontology (PO). This file is created by filtering plant_ontology_assert.obo to contain only terms from the plant structure development stage branch of the PO. For more information, please see: http://palea.cgrb.oregonstate.edu/viewsvn/Poc/tags/live/

Proper citation: Plant Structure Development Stage (RRID:SCR_010410) Copy   

•   Source: SciCrunch Registry

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

An ontology based on the papers Toward an Ontological Treatment of Disease and Diagnosis and On Carcinomas and Other Pathological Entities to address some of the issues raised at the Workshop on Ontology of Diseases (Dallas, TX) and the Signs, Symptoms, and Findings Workshop (Milan, Italy). OGMS was formerly called the clinical phenotype ontology. Terms from OGMS hang from the Basic Formal Ontology.

Proper citation: Ontology for General Medical Science (RRID:SCR_010384) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/TOP-MENELAS

Ontology to (i) Provide better account of and better access to medical information through natural languages in order to help physicians in their daily practice, and to (ii) Enhance European cooperation by multilingual access to standardised medical nomenclatures. The major achievements of MENELAS are the realization of its two functional systems: (i) The Document Indexing System encodes free text PDSs into both an internal representation (a set of Conceptual Graphs) and international nomenclature codes (ICD-9-CM). Instances of the Document Indexing System have been realised for French, English and Dutch ; (ii) The Consultation System allows users to access the information contained in PDSs previously indexed by the Document Indexing System. The test domain for the project was coronary diseases. The existing prototype shows promising results for information retrieval from natural language PDSs and for automatically encoding PDSs into an existing classification such as ICD-9-CM. A set of components, tools, knowledge bases and methods has also been produced by the project. These include language-independent ontology and models for the domain of coronary diseases; conceptual description of the relevant ICD-9-CM codes. This ontology includes a top-ontology, a top-domain ontology and a domain ontology (Coronay diseases surgery). The menelas-top ontology here is the part of the whole ontology without any reference to medical domain.

Proper citation: Menelas Project Top-Level Ontology (RRID:SCR_010356) Copy   

•   Source: SciCrunch Registry

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

An application ontology for microRNAs.

Proper citation: MicroRNA Ontology (RRID:SCR_010360) Copy   

•   Source: SciCrunch Registry

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

Ontology that provides a comprehensive description of the existing microbial typing methods for the identification of bacterial Isolates and their classification. Such a description constitutes an universal format for the exchange of information on the microbial typing field, providing a vehicle for the integration of the numerous disparate online databases. In its current version, TyPon describes most used microbial typing methods but it is, and always will be, a work in progress given the constant advances in the microbial typing field.

Proper citation: Microbial Typing Ontology (RRID:SCR_010362) 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