the umls semantic network support for semantic integration and reasoning
Download
Skip this Video
Download Presentation
The UMLS Semantic Network Support for semantic integration and reasoning

Loading in 2 Seconds...

play fullscreen
1 / 57

The UMLS Semantic Network Support for semantic integration and reasoning - PowerPoint PPT Presentation


  • 148 Views
  • Uploaded on

The UMLS Semantic Network Support for semantic integration and reasoning. Workshop UMLS Semantic Network NLM, NIH, Bethesda, 7-8 Apr 2005 Anita Burgun. Overview. Semantic integration Role of the SN Integration of resources Integration of data Reasoning Reasoning with hierarchies

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' The UMLS Semantic Network Support for semantic integration and reasoning' - hetal


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
the umls semantic network support for semantic integration and reasoning

The UMLS Semantic NetworkSupport for semantic integration and reasoning

Workshop UMLS Semantic Network

NLM, NIH, Bethesda, 7-8 Apr 2005

Anita Burgun

overview
Overview
  • Semantic integration
    • Role of the SN
    • Integration of resources
    • Integration of data
  • Reasoning
    • Reasoning with hierarchies
    • Reasoning with associative relations
  • Perspectives
  • Illustration
    • Genes, gene products, diseases
    • Findings, signs, diseases
semantic integration

Semantic integration

1- Role of ontologies

integration

Mediation system

Ontologies

Integration

DWH

Gene instances

Data Warehouse

Local res.

External resources

Micro-arraydata

Patient

files

…..

GEN

BANK

SWISS

PROT

MED

LINE

GOA

integrating data in the domain of organ failure and transplantation
Integrating data in the domain of organ failure and transplantation

EfG

transplantation

REIN

End stage renal failure

EfG terminology server

dialysis

Local

Information Systems

slide6

M

A

P

P

I

N

G

ONTO-

TERM

T1

T2

mapping

term-term

T3

Metathesaurus

Semantic Network

semantic integration1

Semantic integration

2- Resource Integration

integration1

Mediation system

Ontologies

Integration

DWH

Gene instances

Data Warehouse

Local res.

External resources

Micro-arraydata

Patient

files

…..

GEN

BANK

SWISS

PROT

MED

LINE

GOA

introduction

<OrgName>

<OrgName_name>

<OrgName_name_binomial>

<BinomialOrgName>

<BinomialOrgName_genus>Homo</BinomialOrgName_genus>

<BinomialOrgName_species>sapiens</BinomialOrgName_species>

</BinomialOrgName>

</OrgName_name_binomial>

</OrgName_name>

<OrgName_lineage>Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;

Mammalia; Eutheria; Primates; Catarrhini; Hominidae; Homo</OrgName_lineage>

<OrgName_gcode>1</OrgName_gcode>

<OrgName_mgcode>2</OrgName_mgcode>

<OrgName_div>PRI</OrgName_div>

</OrgName>

<ORGANISM>Homo sapiens</ORGANISM>

<TAXONOMY>Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;Mammalia;

Eutheria; Primates; Catarrhini; Hominidae; Homo.</TAXONOMY>

Introduction

<OrgName>

<OrgName_name>

<OrgName_name_binomial>

<BinomialOrgName>

<BinomialOrgName_genus>Homo</BinomialOrgName_genus>

<BinomialOrgName_species>sapiens</BinomialOrgName_species>

</BinomialOrgName>

</OrgName_name_binomial>

</OrgName_name>

<OrgName_lineage>Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi;

Mammalia; Eutheria; Primates; Catarrhini; Hominidae; Homo</OrgName_lineage>

<OrgName_gcode>1</OrgName_gcode>

<OrgName_mgcode>2</OrgName_mgcode>

<OrgName_div>PRI</OrgName_div>

</OrgName>

  • Increasing need for physicians and biologists to access information on the Internet
  • Biomedical sources
    • Scattered
    • Multiple heterogeneity
    • Rapid evolution and frequent creation
  • Integration
objectives
Objectives
  • Overall: creating a system
    • Global access
    • Homogeneous and up-to-date information
  • Specific: acquiring sources schemas
    • As automatically as possible
    • Dealing with updates, adding new resources
    • Generate different paths to access information
sources schema
Sources schema
  • Rarely available or hard to exploit
  • No existing standard
  • Identifying the schema of each source by exploiting its contents
    • Informs on the type of information present in the source
    • Extraction from its Web site
use of umls
Use of UMLS
  • Heterogeneity of schemas
  • Need of a common vocabulary: the UMLS
  • Example : finding the site of expression of a gene starting from a gene symbol
results
Results
  • 279 distinct terms extracted from 11 sources
    • 232 found in the UMLS corresponding to 495 MTH concepts
      • 318 were correct
      • 177were not
    • 47 not found
  • Of the 318 MTH concepts, 60 concepts are common to at least 2 distinct extracted terms (158 are specific)
mapping ult to the umls
Mapping ULT to the UMLS
  • General concepts
    • Citation -> Organism attribute
    • Description -> Research activity
    • Symbol -> Idea or Concept
    • Name -> Intellectual product
    • History -> Finding
    • Matches -> Manufactured object
    • Link -> Chemical Viewed Structurally
    • Association -> Mental Process/ Social Behavior
general concepts
General concepts

General classes

« Metaterms »

WordNet??

Upper Level

Ontology

General

Ontology

Idea or Concept

Intellectual Product

Attributes

Functional/Spatial/

Temporal Concept

Domain

Ontology

semantic integration2

Semantic integration

3- Data Integration

functional genomics
Functional genomics
  • Post genomics
  • Gene expression, protein function, biological process, disease
  • van de Vijver MJ et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002 Dec 19; 347(25): 1999-2009.
  • Objective : provide « medical » annotation of genes (BioMeKe)
  • GeneTraces (Cantor, Lussier)
gene gene product disease
Gene, gene product, disease
  • HUGO : manage heterogeneity of data
  • Superoxide dismutase 1, soluble/ amyotrophic lateral sclerosis 1 (adult)
  • C1420306 SOD1 gene (symbol) gene or Genome
  • C0669516 SOD1 gene product (symbol) Amino acid, protein
  • C0002736 ALS (previous symbol) Disease or Syndrome
  • No relation in MTH
gene gene product disease1
Gene, gene product, disease
  • HUGO
  • Aconitase 1, soluble
  • C1412126 ACO1 gene (symbol) gene or Genome
  • C0378502 ACO1 protein (symbol)/ IRP 1 protein (alias)
  • Amino acid, protein
  • OR relation between the two concepts in MTH
gene gene product disease2
Gene, gene product, disease
  • HUGO synonymous terms

T1

T2

T3

ST2

C2

ST3

ST1

C1

C3

gene gene product disease3
Gene, gene product, disease

Gene or Genome

produces

location_of

AA, protein

Disease or Syndrome

affects

causes

reasoning1
Reasoning

SN relations

categorization

reasoning relations

Reasoning : relations

1- The hierarchy and the economy principle

the economy principle
The economy principle
  • R1. Ad hoc precision
    • The intent is to establish a set of semantic types, which will be useful for a variety of tasks without introducing undue complexity. The most specific semantic type in the semantic type hierarchy is assigned to the concept.
  • R2. No hybrid types
    • Instead of creating a lattice structure, with hybrid types inheriting from two supertypes, the SN has a single inheritance tree structure. As a consequence, a Metathesaurus concept inheriting from two STs is assigned to both types.
  • R3. No category “other”
    • Rather than proliferating the number of semantic types to encompass multiple additional subcategories, concepts that cannot be categorized by any sibling Semantic Type are simply assigned their common supertype.
the economy principle and the theory
The economy principle and the theory
  • Intensions and extensions
    • Taxonomies (isa) are systems in which categories (intensions) are related to one another by means of subordination, or, in class parlance (extensions), systems in which classes are related to one another by means of class inclusion.
  • Categories and classes
    • When a category K has subcategories K1, K2, …. Kn, its extension, the class CK is the union of the classes for each of its subcategories, i.e. CK1, CK2,……CKn.
slide31

Categories

Manufactured Object

physical object made by human beings

Medical Device

Research Device

Clinical Drug

Manufactured object used primarily in the diagnosis, treatment, or prevention of physiologic or anatomic disorders

Manufactured object used primarily in carrying out scientific research or experimentation

Pharmaceutical preparation as produced by the manufacturer

CMD

CRD

CCD

CMD CRD CCD

CMO

45 inch calibre bullet

magnetic tape, matches, corridor

Classes

reasoning relations1

Reasoning : relations

2- Associative relations

diseases and findings
Diseases and Findings

Event

Entity

Natural phenomenon

or process

Conceptual entity

Finding

Pathologic function

Sign or Symptom

Disease or syndrome

diseases and findings sn

Associated_with

Evaluation_of

Manifestation_of

Diseases and Findings: SN

Finding

is_a

Sign or Symptom

Disease or syndrome

Diagnoses

relations sn
Relations SN
  • Disease or Syndrome affects Disease or Syndrome
  • Disease or Syndrome associated_with Disease or Syndrome
  • Disease or Syndrome co-occurs_with Disease or Syndrome
  • Disease or Syndrome complicates Disease or Syndrome
  • Disease or Syndrome degree_of Disease or Syndrome
  • Disease or Syndrome manifestation_of Disease or Syndrome
  • Disease or Syndrome occurs_in Disease or Syndrome
  • Disease or Syndrome precedes Disease or Syndrome
  • Disease or Syndrome process_of Disease or Syndrome
  • Disease or Syndrome result_of Disease or Syndrome
relations in snomed ct vs sn
Relations in SNOMED CT vs SN
  • Class ASNCT = SNCT concepts assigned to the Semantic Type A
  • Class DISEASESSNCT = SNCT concepts assigned to ‘Diseases or Syndrome’

A

B

C

MTH restricted to SNCT

relations in snomed ct
Relations in SNOMED CT
  • MTH restricted to SNOMED CT
  • Relations whose SAB = SNOMED CT
  • 2,220,144 relations
  • 1,392,380 associative relations (including inverse relations)
  • 113 associative relationships (all have inverse except associated_with)
  • 18 relationships have less than 100 instances
    • Has_time_aspect_of : 1
    • Has_property : 77
  • The most frequent :
    • Has_onset : 114,173
    • has_finding_site : 99,156
    • has_method : 70,682
relations in snomed ct1
Relations in SNOMED CT
  • Focus on Diseases and Findings
  • Class DISEASESSNCT = SNCT concepts assigned to ‘Disease or Syndrome’
  • Class FINDINGSSNCT = SNCT concepts assigned to {‘Finding’ + ‘Sign or Symptom’}

Finding

Disease or Sd

Sign or symptom

MTH restricted to SNCT

diseases diseases relations snct
due_to

definitional_manifestation_of

associated_with

occurs_before

mapped_to

has_finding_site

has_associated_finding

interprets

has_associated_morphology

Diseases-Diseases relations SNCT
diseases diseases relations snct sn
due_to

definitional_manifestation_of

associated_with

occurs_before

mapped_to

has_finding_site

has_associated_finding

interprets

has_associated_morphology

result_of

manifestation_of

associated_with

precedes , occurs_in, complicates?

co-occurs_with

degree_of

process_of

affects

Diseases-Diseases relations SNCT/SN

SNCT

SN

findings diseases relations snct
has_associated_finding / associated_finding_of

has definitional manifestation/ definitional_manifestation_of

interprets / is_interpreted_by/ has_interpretation

occurs_after / occurs_before

mapped_to /mapped from

has_associated_morphology / associated_morphology_of

due_to / cause_of

focus_of

has_finding_site

isa / inverse is-a

Findings-Diseases relations SNCT
diseases findings relations snct sn
has_associated_finding / associated_finding_of

has definitional manifestation/ definitional_manifestation_of

interprets / is_interpreted_by/ has_interpretation

occurs_after / occurs_before

mapped_to /mapped from

has_associated_morphology / associated_morphology_of

due_to / cause_of

focus_of

has_finding_site

isa / inverse is-a

associated_with

manifestation_of

diagnoses

evaluation_of

Diseases-Findings relations SNCT/SN

SNCT

SN

diseases and findings1

Associated_with

Evaluation_of

Manifestation_of

Diseases and Findings

Finding

is_a

Is_a

5,592 instances

Sign or Symptom

Disease or syndrome

Diagnoses

diseases and findings2
Diseases and Findings

Event

Entity

Natural phenomenon

or process

Conceptual entity

Finding

Pathologic function

Sign or Symptom

Disease or syndrome

diseases and findings3
Diseases and Findings

Finding

Disease or syndrome

Sign or Symptom

C1300028

Disorder characterizedby pain

is_a

C0000727

Abdomen, acute

diseases and findings4
Diseases and Findings

C0008767

Scar

Finding

has_finding_site

C1300028

Endometriosisin scar of skin

Sign or Symptom

Disease or syndrome

diseases and findings5
Diseases and Findings

Event

Entity

Natural phenomenon

or process

Conceptual entity

Finding

Pathologic function

Sign or Symptom

Disease or syndrome

formal properties
Formal properties
  • Guarino, Welty
  • Rigidity
    • property that is essential to all the instances.Person (+R). Physician (not R).
  • Identity
    • there is a property that is both necessary and sufficient for identifying an instance. Person (+I)
  • Unity
    • instances are intrinsic wholes. Person (+U).
  • Dependence
    • for all the instances x, necessarily some instance of Z must exist, which is not a part of x, nor a constituent of x (+D). Food (+D)
formal properties rules
Formal properties Rules
  • Rules
    • (not U) cannot subsume (+U)e.g., Substance cannot subsume Physical Object
    • […]
  • Distinction between roles and sortal types
    • Roles: (Not Rigid) (+Dependent)
    • Sortal types : (+Rigid) (Not Dependent)
formal properties signs
Formal properties: signs
  • Signs or Symptoms are Roles
  • Metathesaurus concepts that are assigned only to roles with no sortal Semantic Type represent a numerous set of entities
  • About 90% of the MTH concepts assigned to Findings, and Signs or Symptoms are not assigned to another Semantic Type.
roles vs relations
Roles vs relations
  • Findings?
  • Sign or Symptom associated_with Disease or Syndrome
  • Sign or Symptom diagnoses Disease or Syndrome
  • Sign or Symptom evaluation_of Disease or Syndrome
  • Sign or Symptom manifestation_of Disease or Syndrome
  • Finding associated_with Disease or Syndrome
  • Finding evaluation_of Disease or Syndrome
  • Finding manifestation_of Disease or Syndrome
diseases frames
Diseases: frames
  • Has_location
  • Has_lesion : necrosis
  • Has_process : infection
    • (has_agent)
  • Has_discriminating_sign_or_finding
    • hematuria
  • Occurs_in
perspectives 1 coverage
Perspectives (1) : coverage
  • Extend the SN ???
    • Economy principle vs adding general concepts
  • Resource integration ???
    • Needs in BIOmedical
    • Clarify conceptual entities
    • Semantic Types corresponding to general entities
perspectives 2 compatibility
Perspectives (2) : compatibility
  • Compatibility with general ontologies
      • Semantic web
  • Alignment with existing domain ontologies
      • FMA (Zhang Medinfo 2004)
      • SNOMED CT (Burgun ongoing work on SN relations)
  • Rules (classification), consistency SN-MTH
      • E.g. sign or symptom is-a disease
perspectives 3 formal aspects
Perspectives (3): formal aspects
  • Formal ontology
    • Make relations and concepts more explicit, e.g. roles (ULO), relationships between genes and diseases
    • Cohérence, e.g. is-a relations between findings and diseases (studies and processing)
    • Classification of new concepts, e.g upper MTH concepts (Bodenreider Medinfo 2004)
    • Inference, e.g. use relations between anatomical sites and diseases to suggest new relations between diseases (Burgun submitted AMIA 2005)
references
References
  • Mougin F, Burgun A, Loreal O, Le Beux P. Towards the automatic generation of biomedical sources schema. Medinfo. 2004;2004:783-7.
  • Welty C, Guarino N. Supporting Ontological Analysis of Taxonomic Relationships (2001)  Data Knowledge Engineering, http://www.ladseb.pd.cnr.it/infor/Ontology/Papers
  • Zhang S, Bodenreider O. Comparing Associative Relationships among Equivalent Concepts Across Ontologies. Medinfo. 2004;2004:459-66.
ad