1. Mouse BIRN: Ontologies Maryann Martone and Bill Bug 2005 All Hands Meeting Mouse BIRN: Ontologies Maryann Martone and Bill Bug

2. Use of Ontologies in BIRN Databases Enforces semantic consistency within a database Data Sharing Establishes semantic relationship among concepts contained in distributed databases Data integration Bridging across multiscale and multimodal data Concept-based queries : Ontologies can be used to alter semantic context to present a view of the conceptual aspects of a data set or meta-analysis result most relevant to a particular neuroscientist

3. BIRN Ontolgy Working Group Agenda Overview (Maryann) Introduction to the UMLS (Carol) Introduction to Gene Ontology (Bill) Discussion Break Current Test Bed experiences with Ontologies –Mouse BIRN (Maryann) –Function BIRN (Jessica) –Morph BIRN (Christine) Panel discussion (Ontology Task Force): what areas of interest to BIRN are not adequately covered by existing ontologies, including discussion of mapping animal models onto human disease (Part 1) Wrap Up Day 2: Data Integration and Ontologies

4. Objectives of Working Group Educate BIRN participants on the use of ontologies and associated tools for data integration –Tuesday (PM) and Wednesday (AM) Develop a set of ontology resources for BIRN participants, based on existing ontologies where possible Identify areas that are not well covered by existing ontologies for possible development. ***Develop a clear set of policies and procedures for working with ontologies –Including curation, addition of core ontologies, extension of ontologies, mapping of databases to ontologies

5. The Ontology Task Force  Carol Bean (co-chair), NIH-NCRR  Maryann Martone (co-chair), Mouse BIRN, BIRN CC  Amarnath Gupta, BIRN CC  Bill Bug, Mouse BIRN  Christine Fennema-Notestine, Morph BIRN  Jessica Turner, FBIRN Jeff Grethe, BIRN CC

6. Goals of OTF Provide a dynamic knowledge infrastructure to support integration and analysis of BIRN federated data sets, one which is conducive to accepting novel data from researchers to include in this analysis. Identify and assess existing ontologies and terminologies for summarizing, comparing, merging, and mining datasets. Relevant subject domains include clinical assessments, demographics, cognitive task descriptions, imaging parameters/data provenance in general, and derived (fMRI) data. Identify the resources needed to achieve the ontological objectives of individual test-beds and of the BIRN overall. May include finding other funding sources, making connections with industry and other consortia facing similar issues, and planning a strategy to acquire the necessary resources.

7. BIRN Ontology Resources Mouse BIRN Ontology Resource Page http://nbirn.net/Resources/Users/Ontologies/ Bonfire Ontology Browser and Extension Tool

8. Current Ontology Development by Mouse BIRN Participants Developmental Ontology Seth Ruffins, Cal Tech Subcellular Anatomy Maryann Martone and Lisa Fong, UCSD

9. Ontology for Subcellular Anatomy of Nervous System

10. CCDB Dictionary TermOntologyConceptIDSemantic TypeDefinition CerebellumUMLSC0007765Body Part, Organ, or Organ Component Part of the metencephalon that lies in the posterior cranial fossa behind the brain stem. It is concerned with the coordination of movement. (MSH) Glial Fibrillary Acidic Protein UMLSC0017626 Amino Acid, Peptide, or Protein, Biologically Active Substance An intermediate filament protein found only in glial cells or cells of glial origin. MW 51,000. (MSH) Medium Spiny Neuron BonfireBID000012CellSmall (10-15 µm in diameter) projection neurons found in neostriatum, possessing a rougly spherical dendritic tree composed of 3-5 primary dendrites. Dendrites are covered with dendritic spines. Purkinje cellUMLS C0034143 Cell large branching neurons of the middle layer of cerebellar cortex, characterized by vast arrays of dendrites; the output neurons of the cerebellar cortex.

11. Bonfire: Collaborative Building and Extension of Ontologies

12. Registered to Term Index Source of Mediator

13. Some Areas of Interest to BIRN Navigating through Multi-resolution information Linking animal and human imaging data brain cerebellum cerebellar cortex Purkinje cell dendritic spine Entopeduncular nucleus Globus pallidus, internal segment Animal Model Disease Process ***Map between Human and Animal models Functional assessment

14. Anatomical Knowledge Sources Foundational model of anatomy Neuronames (Brain Info)*** BAMS*** Adult Mouse Anatomical Dictionary (Edinburgh/GO) “Although BIRN is an open, diverse and fluid environment, the use of ontologies for enhanced interoperability will be pointless if we allow random use of ontologies. The OTF recommends that there be a set of ontologies that are approved for use and a set of policies and procedures for adding or creating additional knowledge sources. Current knowledge sources that are currently in use include UMLS, GO, LOINC, SNOMED, NEURONAMES.” -OTF report to BEC 8/05

15. Other Resources Likely of Use Mouse Phenome Project: a collection of phenotypic and genotypic data for the laboratory mouse anatomy behavior biological factors blood cancer diet effects drug effects, toxicity genotype heart, lung intake, metabolism musculoskeletal neurosensory reproduction acoustic startle response activity and motor function adrenal, thymus, kidney anxiety atherogenic diet avoidance blood calcium and pH blood coagulation factors body composition body weight bone mineral density and content brain measurements cardiovascular cholesterol craniofacial measurements disease susceptibility drinking preference electroconvulsive threshold ethanol effects exploratory behavior food and water intake gallbladder and gallstones glucose. hearing hematology hormones lipids lipoproteins liver lungs metabolism metastatic progression MHC H2 haplotype nociception organ weights pathology images peptides and proteins prepulse inhibition reproductive performance SNPs and other polymorphisms strength toxicity triglycerides wildness

16. Neuronames-UMLS-Smart Atlas Mapping of rodent nomenclature onto UMLS Neuronames has now included many of the terms Using concepts in Neuronames and Paxinos to create new hierarchy

17. What do we need to do in the next year Identify areas of mouse BIRN not covered –Do ontologies exist? –If not, do we develop them What known ontologies should be added to BIRN ontology resources –Who will handle semantic concordance –How do we represent these in BIRN? Mapping databases to ontologies –Time frame –What should be mapped? –Who will do this at each site

18. Mouse BIRN Global Conceptual Schema Project Experimental Data Molecular Distributions Subject Animal Type Experiments Anatomical Properties Microarray Results Images Atlas Region of Interest Worked with Data Integration group to define global schema