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Terms associated with pediatrics, representing information related to child health and development from pre-birth through 21 years of age; contributed by the National Institute of Child Health and Human Development.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology for representing data mining investigations. Its goal is to allow the representation of knowledge discovery processes and be general enough to represent the data mining investigations. The ontology is based on the CRISP-DM process methodology.

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• SciCrunch
• 13 years ago - by Anonymous

Generic ontology for the domain of data mining that includes the information processing processes that occur in the domain of data mining, participants in the processes and their specifications. OntoDM is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. The generality in scope allows wide number of applications of the ontology, such as semantic annotation of data mining scenarios, ontology based support for QSARs, etc.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology to support systematic description of, and interoperable queries on, human studies and study elements.

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• SciCrunch
• 13 years ago - by Anonymous

A biomedical ontology in the domain of biological and clinical statistics that is primarily targeted for statistical representation in the fields in biological, biomedical, and clinical domains. It uses the Basic Formal Ontology (BFO) as the upper level ontology. OBCS imports all biostatistics related terms in the Ontology for Biomedical Investigations (OBI) including all logical axioms.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology for common concepts for communication between traditional medicine and western medicine. (In French)

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• SciCrunch
• 13 years ago - by Anonymous

Application ontology covering the domain of newborn screening, follow-up and translational research pertaining to patients diagnosed with inheritable and congenital diseases mainly identified through newborn dried blood spot screening. ONSTR is a central component of the project Newborn Screening Follow-up Data Integration Collaborative (NBSDC), https://nbsdc.org. ONSTR uses the Basic Formal Ontology v2 (BFO2, v2012-07-20) as top-level ontology and extends the classes imported from OBO Foundry ontologies and candidate ontologies.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology designed around the guiding concept of a symptom being: A perceived change in function, sensation or appearance reported by a patient indicative of a disease. Understanding the close relationship of Signs and Symptoms, where Signs are the objective observation of an illness, the Symptom Ontology will work to broaden it''s scope to capture and document in a more robust manor these two sets of terms. Understanding that at times, the same term may be both a Sign and a Symptom

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• SciCrunch
• 13 years ago - by Anonymous

Ontology to establish data exchange standards and common data elements in the microRNA (miR) domain. Biologists (cell biologists in particular) and bioinformaticians can make use of OMIT to leverage emerging semantic technologies in knowledge acquisition and discovery for more effective identification of important roles performed by miRs in humans'' various diseases and biological processes (usually through miRs'' respective target genes). OMIT has reused and extended a set of well-established concepts from existing bio-ontologies, e.g., Gene Ontology, Sequence Ontology, Protein Ontology, NCBI Organism Taxonomy, Human Disease Ontology, Foundational Model of Anatomy, and so forth.

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• SciCrunch
• 13 years ago - by Anonymous

Application ontology to model / represent the notion of genetic susceptibility to a specific disease or an adverse event or a pathological biological process. It is developed using BFO2.0''s framwork. The ontology is under the domain of genetic epidemiology.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology used to model the scientific investigation, especially Genome-Wide Association Study (GWAS), to find out genetic susceptibility factor to disease, such as Diabetes. It models the genetic varaints, polymorphisms, statistical measurement, populations and other elements that are essential to determine a genetic susceptibility factor in GWAS study. It must be used with other two ontologies, in the case of Diabetes, :Ontology of Geographical Region (OGR) and Ontology of Glucose Metabolism Disorder (OGMD) .

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• SciCrunch
• 13 years ago - by Anonymous

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.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology for the description of drug discovery investigations. DDI aims to follow to the OBO (Open Biomedical Ontologies) Foundry principles, uses relations laid down in the OBO Relation Ontology, and be compliant with Ontology for biomedical investigations (OBI).

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• SciCrunch
• 13 years ago - by Anonymous

An ontological knowledge base model for cystic fibrosis. There are molecular genetic information (i.e. gene mutations) and health information included in OntoKBCF. The purposes of OntoKBCF include management of molecular genetic information and health information and embedding OntoKBCF into EHR settings.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology that contains activities that nurses use while coordinating care among patients.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology to help the systematic review and meta-analysis process of non randomized clinical trials.

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• SciCrunch
• 13 years ago - by Anonymous

Species taxonomy for the data curated in NeuroMorpho.Org. The existing ontologies are re-used as needed as the new metadata information for species and strains is deposited in NeuroMorpho.Org database. This species hierarchy consists of 56% of NCBI taxonomy and 39% of Rat strain ontology. The remaining 5% mostly consists of new concepts and few others from NIFSTD and MESH.

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• SciCrunch
• 13 years ago - by Anonymous

Species ontology that adopts and integrates relevant portions of available taxonomies as needed based on the species and strain terms represented in the current release of NeuroMorpho.Org (72 terms as of the 5.7 release) and any future additions. When a NeuroMorpho.Org term is mapped with an external resource, its entire lineage (ancestors and descendants) is added to the NeuroMorpho.Org species ontology. The resulting 1,340 terms of this initial version of the ontology come for 65% from the NCBI taxonomy (24 NeuroMorpho.Org species/strain terms mapped), 30% from the Rat Gene Database (1 term mapped), and altogether 5% from NIFSTD (7 terms mapped), MeSH (2 terms mapped), ITIS (1 term mapped), and custom-added concepts (41 terms mapped, largely mouse strains from Jackson Labs).

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• SciCrunch
• 13 years ago - by Anonymous

Ontology of neural functional motor recovery.

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• SciCrunch
• 13 years ago - by Anonymous

Ontology that describes the medical information necessary for early detection of the oral cancer reoccurrence extracted from the NeoMark Project.

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• SciCrunch
• 13 years ago - by Anonymous