All Hands Meeting 2003

BIRN ONTOLOGIES Session

Jeffrey Grethe

Amarnath Gupta

Bertram Ludäscher

Maryann E. Martone

Overview

First half:• Ontologies (brief; not a “total recall”) (Bertram)• UMLS & “Bonfire” extensions (Jeff)• Disease maps (Maryann, Amarnath)• Ontology-enhanced tools (Maryann)

Second half:• Discussion on policy issues, BIRN ontology curation etc

Kinds of “Ontologies” (simplified cheat sheet)

1. Controlled Vocabularies agreed upon range of values (“enumeration type”) e.g. “standard names” for materials, diseases, …

2. Simple Taxonomies, Classification hierarchies (isa) controlled concept vocabulary

+ subconcept (specialization) relationship e.g. biological taxonomies

3. Graph-like Ontologies isa, has-a, and other relationships

(contained_in, causes, activates, …),

the latter usually w/o formalized semantics (but agreed upon) e.g. semantic nets, RDF, …

4. Full-fledged Ontologies Usually logic-based ontologies; relationships (including isa) are logic consequences of

formal concept definitions (partially) defined semantics

You knew this already: e.g. 5. Conceptual Models DSM-IV(Diagnostic and Statistical Manual of Mental Disorders )

290.11 isa 290.1 isa 290

concept conceptrelationship

conceptconceptconcept

concept concept

isa

concept

Parent Personoffspring.Person

class class

class

relation

part-of

DSM IV Taxonomy

290 Dementia of the Alzheimer's Type, With Late Onset, Uncomplicated

290.1 Dementia Due to Creutzfeldt-Jakob Disease

290.1 Dementia Due to Pick's Disease

290.1 Dementia of the Alzheimer's Type, With Early Onset, Uncomplicated

290.11 Dementia of the Alzheimer's Type, With Early Onset, With Delirium

290.12 Dementia of the Alzheimer's Type, With Early Onset, With Delusions

290.13 Dementia of the Alzheimer's Type, With Early Onset, With Depressed Mood

290.2 Dementia of the Alzheimer's Type, With Late Onset, With Delusions

290.21 Dementia of the Alzheimer's Type, With Late Onset, With Depressed Mood

290.3 Dementia of the Alzheimer's Type, With Late Onset, With Delirium

290.4 Vascular Dementia, Uncomplicated

290.41 Vascular Dementia, With Delirium

290.42 Vascular Dementia, With Delusions

290.43 Vascular Dementia, With Depressed Mood

291 Alcohol Intoxication Delirium

Uses of Ontologies in Data Integration

“Smart” (conceptual-level) data discovery, browsing, querying • looking for “C”, finding “D” (which is C-related)• terminological and semantic “glue” between different “data worlds”

Conceptual / Semantic Modeling of a domain• for terminologies: “domain maps” (in description logic)• for processes: “process maps”, “disease maps” (open issue)

…

Need to provide …• Ontology exchange syntax • Ontology extensions mechanisms ( BONFIRE)• Inter-ontology mapping mechanisms (yours vs. mine)• Data-to-ontology registration mechanisms (data to concepts)

Generic Standards

RDF, RDFS• For graph-based ontologies (=explicit statements)

OWL (Web Ontology Language)

• Three levels: OWL Lite, OWL DL, OWL Full• Some Features:

Ontology O2 uses (refers to) O1 (over the web!)

formalism to exchange, extended, and map between ontologies

concept conceptrelationship

Parent Personoffspring.Person

Generic Tools Ontology authoring: Protégé-2000 ontology tool (Stanford)

• OWL Plug-In (evolving)

Developers’ corner:• Jena-2 Semantic Web Framework (HP), for dealing with OWL ontologies• Logic programming extensions (SWI)

Example: Ontology-enhanced Map Integration (OMI)

1. Upload ontologies O1, O2, … (O2, O3 use O1,…)

2. Upload ontology mapping Om :: Oa Ob

3. Register data sets D1, D2, … to ontology Oa

4. Query data sets through Ob interface!

UMLS &

BONFIRE (Community Ontology Building)

What is UMLS?

UMLS is a long-term research project began on 1986 by the National Library of Medicine (NLM)

UMLS is a collection of knowledge sources designed to facilitate the retrieval and integration of information from multiple machine-readable biomedical information sources

Knowledge Resources

Metathesaurus • The Metathesaurus is organized by concept or meaning, it

provides a uniform, integrated distribution format from about 60 biomedical vocabularies and classifications and links many different names for the same concepts

• The 2000 edition of the Metathesaurus includes more than 730,000 concepts and 1.5 million concept names from over 50 different biomedical vocabularies, some in multiple languages

Knowledge Resources

Semantic Network • Semantic Network contains information about the types or

categories (e.g., "Disease or Syndrome," "Virus") to which all concepts have been assigned and the permissible relationships among these types (e.g., "Virus" causes "Disease or Syndrome")

• The semantic types are the nodes in the Network, and the relationships between them are the links.It has 132 semantic types, 53 links between the semantic types.

Knowledge Resources

Semantic Network • Semantic types: organisms, anatomical structures,

biologic function, chemicals, events, physical objects, and concepts or ideas etc.

• Relations: ‘isa’, `physically related to,' `spatially related to,' `temporally related to,' `functionally related to,' and `conceptually related to’ etc.

Hierarchical relations types:

Associative (non-isa) Relationships

Knowledge Resources

Information Sources Map• The information sources are varied and include

bibliographic databases, diagnostic expert systems, and factual databases

• The Information Sources Map or directory contains both human-readable and machine-"processable" information about the scope, location, vocabulary, syntax rules, and access conditions of biomedical databases of all kinds

Related Sites

Further Information:

http://www.nlm.nih.gov/ http://www.nlm.nih.gov/research/umls/ http://www.nlm.nih.gov/research/umls/UMLSDOC.HTML http://www.nlm.nih.gov/research/umls/umlsmain.html

BONFIRE

BONFIRE will allow BIRN users to accommodate concepts not present in the available pre-defined source ontologies

Whenever possible, users should employ the relationship terms provided within the UMLS or other source ontologies provided by BIRN

Once new terms are defined, when will they will become part of the BIRN Ontology (BONFIRE)?• after appropriate curation?

Ontology Refinement

An Example Data Set

species = rat (UMLS: C003493) region = neostriatum (UMLS: C0162512) cell type = medium spiny cell (No Concept Available) structure = spiny dendrite(No Concept Available) segmented object = dendritic spine (UMLS:

C0872341) segmented object = dendritic shaft (No Concept

Available)

BONFIRE Example

For this data set, no ontology IDs exist for medium spiny cell, spiny dendrite or dendritic shaft.

medium spiny cell (BONFIRE: BID006) medium spiny cell “is a” neuron (UMLS: C0027882) medium spiny cell “has location” neostriatum (UMLS: C0162512) medium spiny cell “is a” neuron AND “has property” dendritic spine (UMLS:

C0872341)

spiny dendrite (BONFIRE: BID007) spiny dendrite “is a” dendrite (UMLS: C0011305) spiny dendrite ‘contains” dendritic spine (UMLS: C0872341)

DISEASE MAPS

Glue Knowledge for Mouse 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

•Link database concepts to UMLS/Neuronames

•Utilize the neurohomology ontology: M. Bota at USC

•Develop disease and animal model knowledge maps

Knowledge Maps

Parkinson’s Disease

Pathological feature

Alpha synuclein

Abnormal filaments

Substantia nigra

ubiquitin

symptom

tremorakinesia

rigidity

Motor deficit

neurons

Lewy Body C0085200

C0030567

Cell inclusion C0205708

glia

neuronal degeneration

Dopamine neuron

cortex

Basal forebrain

Filamentous inclusion C0230674

C0815003

C024566

C0027746

C0746626

C027746

C0007776

C0175412

C0041538

C0027882

C0027836

Knowledge Map: Animal Model

a-synuclein mousetransgenic animal

Cellular phenotype

Cellular inclusion

Behavioral phenotype

Alpha synuclein C024566

nuclear inclusion C0544907

Alpha synuclein C024566

Cytoplasmic inclusion C0205708

Motor deficit C0746626

ubiquitin C0041538

neurons gliaC0027882 C0027836

C0025936

Knowledge Maps

Parkinson’s Disease

Pathological feature

Alpha synuclein

neurons

Lewy Body Cytoplasmic inclusion

glia

Filamentous inclusion

a-synuclein mouse

Cellular phenotype

Cellular inclusion

nuclear inclusion

ubiquitin

Alpha synuclein

neurons

Cytoplasmic inclusion

ubiquitin

Parkinson’s disease map

disease C0012634

course of illness C0242656

disease phase C0457338

pathology C0677042

disease characteristic C0599878

symptoms C0683368

Pathological process C0030660

sign/symptom C0037088

proneness/risk C0178598

severities C0439793

epidemiology C0699910

disease classification C0683326

prevention, intervention and treatment C0679677

Parkinson’s disease features

Parkinsons disease has a pathological featurepathological feature is a histopathological featureC0243140Lewy Body C0085200 is a histopathological feature

Lewy Body is a cell inclusion C0205708Lewy Body is a filamentous inclusion C0541641filamentous inclusion C0541641 has part of abnormal filamentabnormal filament consists of alpha synuclein C0245466abnormal filament do not consist of beta synucleinabnormal filament do not consist of gamma synucleinLewy Body contains ubiquitin C0041538Lewy Body has property eosinophilia C0014457Lewy Body has component ParkinLewy Body has componetn synphilin-1Lewy Body has component tauPatients with mutation in parkin do not have Lewy Bodies

Parkinsons disease has a pathological featurepathological feature is a histopathological featureC0243140Lewy Body C0085200 is a histopathological feature

Lewy Body is a cell inclusion C0205708Lewy Body is a filamentous inclusion C0541641filamentous inclusion C0541641 has part of abnormal filamentabnormal filament consists of alpha synuclein C0245466abnormal filament do not consist of beta synucleinabnormal filament do not consist of gamma synucleinLewy Body contains ubiquitin C0041538Lewy Body has property eosinophilia C0014457Lewy Body has component ParkinLewy Body has componetn synphilin-1Lewy Body has component tauPatients with mutation in parkin do not have Lewy Bodies

Concept A relationship Concept B

Parkinson’s disease processes

alpha synuclein protofibrils are toxic to DA neurons; filaments are protective

A53T increases protofilamentsA30P increases protofilamentsA30P inhibits filament formation from protofilamentsprotofibrils permeabilize membranessynaptic vesicles have a membraneprotofibrils permeabilize synaptic vesiclespermeabilization of synaptic vesicles results in leaky vesiclesleaky vesicles in DA neuronsincreased DA in cytoplasm causes cell death

alpha synuclein protofibrils are toxic to DA neurons; filaments are protective

A53T increases protofilamentsA30P increases protofilamentsA30P inhibits filament formation from protofilamentsprotofibrils permeabilize membranessynaptic vesicles have a membraneprotofibrils permeabilize synaptic vesiclespermeabilization of synaptic vesicles results in leaky vesiclesleaky vesicles in DA neuronsincreased DA in cytoplasm causes cell death

Concept A relationship Concept B

Object-Oriented Modeling

TOOLS Custom: Know-ME, OMI, … Generic: Protégé-2000, …

Discussion

Getting Organized

…

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