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Ontologies for Neuroscience and Neurology

Ontologies for Neuroscience and Neurology. The Neuroscience Information Framework Fahim Imam, Stephen Larson, Georgio Ascoli, Gordon Shepherd, Anita Bandrowski , Jeffery S. Grethe , Amarnath Gupta, Maryann E. Martone

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Ontologies for Neuroscience and Neurology

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  1. Ontologies for Neuroscience and Neurology The Neuroscience Information Framework Fahim Imam, Stephen Larson, Georgio Ascoli, Gordon Shepherd, Anita Bandrowski, Jeffery S. Grethe, Amarnath Gupta, Maryann E. Martone University of California, San Diego, George Mason University, Yale University Alexander D. Diehl Alexander P. Cox, Mark P. Jensen, Alan Ruttenberg, Bianca Weinstock-Guttman, KingaSzigiti, and Barry Smith University at Buffalo

  2. NIF Standard Ontologies (NifStd) Bill Bug et al. • Set of modular ontologies • Covering neuroscience relevant terminologies • Comprehensive ~60, 000 distinct concepts + synonyms • Expressed in OWL-DL language • Supported by common DL Resoners • Closely follows OBO community best practices • Avoids duplication of efforts • Standardized to the same upper level ontologies • e.g., Basic Formal Ontology (BFO), OBO Relations Ontology (OBO-RO), Phonotypical Qualities Ontology (PATO) • Relies on existing community ontologies e.g., CHEBI, GO, PRO, OBI etc. • Modules cover orthogonal domain • e.g. , Brain Regions, Cells, Molecules, Subcellular parts, Diseases, Nervous system functions, etc.

  3. NIFSTD External Community Sources

  4. Mental Functioning, Mental Disease, Neurological Disease and Related Ontologies

  5. Neurological Disease Ontology (ND) • Based on the Ontology for General Medical Sciences • Incorporates parts of NIF-Dysfunction • Three initial areas of focus • Dementia, in particular Alzheimer’s Disease • Multiple Sclerosis • Stroke, Cerebrovascular events

  6. Goals • To provide a comprehensive representation of neurological diseases to support clinicians and researchers in the diagnosis, treatment, and study of these diseases. • To facilitate querying of medical databases for such purposes as performing quality analysis checks on diagnostic criteria at various stages of a disease’s progression. • To allow physicians and researchers to provide a comprehensive clinical picture of a patient using a standardized language, and to connect and leverage structured descriptions in clinical and translational medicine, in EHRs and published research. • To develop best practices for the development of other clinically oriented ontologies by identifying a robust set of relations for use with diseases and by providing an applied template for representing temporal entities within a domain.

  7. BFO-OGMS-ND

  8. BFO-OGMS-ND

  9. Diseases

  10. Alzheimer’sDisease

  11. Alzheimer’sDisease

  12. Referenced Ontologies

  13. Status • ND currently contains 335 classes • 199 classes have textual definitions • 52 classes have logical definitions • 157 classes have external references • There are 190 children of disease • First Public release planned by September 2012.

  14. NeuroPsychological Testing Ontology

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