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Ontologies for Neuroscience and Neurology The Neuroscience Information Framework Fahim Imam, Stephen Larson, Georgio Ascoli, Gordon Shepherd, Anita Bandrowski,

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Presentation on theme: "Ontologies for Neuroscience and Neurology The Neuroscience Information Framework Fahim Imam, Stephen Larson, Georgio Ascoli, Gordon Shepherd, Anita Bandrowski,"— Presentation transcript:

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, Kinga Szigiti, and Barry Smith University at Buffalo

2 NIF S TANDARD O NTOLOGIES (N IF S TD ) 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. 2 Modules cover orthogonal domain e.g., Brain Regions, Cells, Molecules, Subcellular parts, Diseases, Nervous system functions, etc. Bill Bug et al.

3 3 NIFSTD E XTERNAL C OMMUNITY S OURCES DomainExternal SourceImport/ AdaptModule Organism taxonomyNCBI Taxonomy, GBIF, ITIS, IMSR, Jackson Labs mouse catalogAdaptNIF-Organism MoleculesIUPHAR ion channels and receptors, Sequence Ontology (SO), ChEBI, and Protein Ontology (PRO); pending: NCBI Entrez Protein, NCBI RefSeq, NCBI Homologene, NIDA drug lists Adapt IUPHAR, ChEBI;Import PRO, SO NIF-Molecule NIF-Chemical Sub-cellularSub-cellular Anatomy Ontology (SAO). Extracted cell parts and subcellular structures. Imported GO Cellular Component ImportNIF-Subcellular CellCCDB, NeuronDB, NeuroMorpho.org. Terminologies; pending: OBO Cell Ontology AdaptNIF-Cell Gross AnatomyNeuroNames extended by including terms from BIRN, SumsDB, BrainMap.org, etc; multi-scale representation of Nervous System Macroscopic anatomy AdaptNIF- GrossAnatomy Nervous system function Sensory, Behavior, Cognition terms from NIF, BIRN, BrainMap.org, MeSH, and UMLS AdaptNIF-Function Nervous system dysfunction Nervous system disease from MeSH, NINDS terminology; Disease Ontology (DO) Adapt/ImportNIF- Dysfunction Phenotypic qualitiesPATO is Imported as part of the OBO foundry coreImportNIF-Quality Investigation: reagentsOverlaps with molecules above, especially RefSeq for mRNAImportNIF-Investigation Investigation: instruments, protocols Based on Ontology for Biomedical Investigation (OBI) to include entities for biomaterial transformations, assays, data transformations AdaptNIF-Investigation Investigation: ResourceNIF, OBI, NITRC, Biomedical Resource Ontology (BRO)AdaptNIF-Resource Biological ProcessGene Ontology’s (GO) biological process in wholeImportNIF-BioProcess Cognitive ParadigmCognitive Paradigm Ontology (CogPO)ImportNIF-Investigation

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

9 Diseases

10 Alzheimer’s Disease

11

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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