describing the quality of knowledge contained in biological and medical knowledge bases mor peleg...

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Describing the Quality of Knowledge Contained in Biological and Medical Knowledge Bases Mor Peleg Department of Management Information Systems University of Haifa The Value of Information in Networked Contexts February 3, 2004

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Describing the Quality of Knowledge Contained in Biological and Medical

Knowledge Bases

Mor PelegDepartment of Management Information

Systems

University of Haifa

The Value of Information in Networked Contexts

February 3, 2004

Knowledge Base (KB)

•KB - a centralized repository for information, stored in machine-readable format, usually on-line

•A KB system contains:–A knowledge model –Tools for information collection,

organization, and retrieval

Components of a biological model

Sequence componentsDB entries

Cellular location

Gene productsNormal/mutated

Biological process

ProteolysisTransportGene regulation

Molecular function

Clinical phenotypes

Goals

•Piece together biological data–Of various types, sources, and quality

•Develop a qualitative model at first–Data is noisy and incomplete

•Create a quantitative model eventually

•Store knowledge to allow–systematic evaluation by scientists – input for computer algorithms

Evaluation of other models

•We evaluated 11 models – from biology, business, and software eng.

•We wanted to combine the best aspects of two of the models

Workflow Biomedical Biological Model + Concept Model Process

Model (TAMBIS+UMLS)•Framework developed using Protégé-

2000

Peleg, Yeh, and Altman, Bioinformatics, vol. 18, pp. 825-837, 2002

Mapping business workflow to biological systems

Business Workflow model Biological Process Model

Process model

Structural modelOrganizational model

Biomolecular complex(Replication complex)

Biopolymer(Helicase)

Role(DNA unwinding)

member

Organizational Unit(Medical School)

Human Role(Dean)

member

Process model

Graphic dynamic & functional model

Queries: All links supported only by speculationAll processes inhibited by neuraminadase and occur in membraneAll mutations that cause misfunctional processes and have clinical phenotype

Mapping to Petri Nets

• Explicitly represent states

• Verification of properties – liveness, boundedness

• Reasoning on dynamics– without t1, can we reach

P4 from P1?

• Simulation

• Which of 2 models is correct?

P1

t1

t4

P2

t2

P3

t3

P4

AND

AND

Conclusion

• Our framework– pieces together qualitative biological data of

various types, sources, and quality– supports identification of the quality of data in

the KB» Useful for identifying areas for more experimentation» Useful to decide which conflicting facts are more

credible

– supports reasoning (queries)– enables verification of dynamic properties and

simulation (prediction)

Representing levels of evidence in clinical guideline models

Thanks!

[email protected]

http://hevra.haifa.ac.il/mis/mor/

Do other models posses the desired properties?

Model graf nesting

static

function

dynamic

bio info verify

Simulation tools

Computational model

Query types*

GO + + - 1,3

TAMBIS + + DL 1,3

EcoCyc + + + + frames 1,2,3

Rzhetsky + + + + frames 1,2,3

State-charts

+ + C + statechart

OMT/UML

+ + + + C +/- statechart

OPM + + + + I +/- Semi-formal

PIF/PSL + I KIF

BPML + C XML

Workflow

+ + + + I + + Petri Nets

Petri Net + + I In some

+ + Petri Nets

DMD: 1,2,4,

5Meta: 2,3

our model

+ + + + I + + + Petri Nets

1-5

C= components, I = integrated * we considered models that can represent biological-specific information

Participant-Role Diagrams

<role>

Individualmolecule

Complex

Collection

Functional

role

Diseaserole

Participants Relations

Rolesrole

Complex-subunit

Collection-participant

Molecule-domain

specialization

Peleg, Gabashvili, and Altman. P IEEE 90(12): 1875-1886, 2002

Queries