Mouse BIRN: Ontologies

Maryann Martoneand

Bill Bug

2005 All Hands Meeting

Mouse BIRN: Ontologies

Maryann Martone and Bill Bug

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

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

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

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

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.

BIRN Ontology Resources

Mouse BIRN Ontology Resource Page

http://nbirn.net/Resources/Users/Ontologies/

Bonfire Ontology Browser and Extension Tool

Current Ontology Development by Mouse BIRN Participants

• Developmental Ontology• Seth Ruffins, Cal Tech

• Subcellular Anatomy• Maryann Martone and Lisa Fong, UCSD

Ontology for Subcellular Anatomy of Nervous System

CCDB DictionaryTerm Ontology ConceptID Semantic Type Definition

Cerebellum UMLS C0007765 Body 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

UMLS C0017626 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

Bonfire BID000012 Cell Small (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 cell UMLS 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.

Bonfire: Collaborative Building and Extension of Ontologies

Registered to Term Index Source of Mediator

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

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

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

Neuronames-UMLS-Smart Atlas

pyramidal cell layer of hippocampus hippocampus C0019564 part ofstratum radiatum of hippocampus hippocampus C0019564 part ofretroethmoid nucleus posterior thalamic group C0175298 part ofrostral linear nucleus of the raphe linear nucleus C0175404 isnucleus of Roller sublingual nucleus C0228552 isrostral periolivary region periolivary nucleus C0175432 part ofretrosplenial agranular cortex cerebral cortex C0007776 part ofretrosplenial granular cortex cerebral cortex C0007776 part ofretrosplenial granular a cortex cerebral cortex C0007776 part ofretrosplenial granular b cortex cerebral cortex C0007776 part ofretrotegmental nucleus of the pons, pericentral part reticulotegmental nucleus of the pons C0175426 part ofprimary somatosensory cortex somatosensory cortex C0037658 part ofpimary somatosensory cortex, barrel field somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, dysgranular region somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, forelimb area somatosensory cortex (primary) C0037658 part ofpimary somatosensory cortex, hindlimb area somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, jaw somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, shoulder/neck region somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, shoulder region somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, trunk region somatosensory cortex (primary) C0037658 part ofprimary somatosensory cortex, upper lip region somatosensory cortex (primary) C0037658 part ofsecondary somatosensory area somatosensory cortex C0037658 part ofscaphoid thalamic nucleus posterior thalamic group C0175298 part ofsuprachiasmatic nucleus, dorsomedial part suprachiasmatic nucleus C0038866 part ofsuprachiasmatic nucleus, ventrolateral part suprachiasmatic nucleus C0038866 part of

•Mapping of rodent nomenclature onto UMLS

•Neuronames has now included many of the terms

•Using concepts in Neuronames and Paxinos to create new hierarchy

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

Mouse BIRN Global Conceptual Schema

Project

ExperimentalData

MolecularDistributions

Subject

Animal Type

Experiments

AnatomicalProperties

MicroarrayResults

Images

Atlas

Region ofInterest

Worked with Data Integration group to define global schema