Prof. dr. Antoine van Kampen

Bioinformatics LaboratoryAcademic Medical Center (AMC)

BioSystems Data Analysis GroupUniversity of Amsterdam

Novel information management approaches for the development of knowledge bases to support systems biology

NCSB meetingFebruary 26, 2009

Data, Information, Knowledge and Wisdom

Data Understanding

Connectedness

Information

Knowledge

Wisdom

Understandingrelations

Understandingpatterns

Understandingprinciples

Data, Information, Knowledge and Wisdom

Data

Information

Knowledge

Wisdom

Data, Information, Knowledge and Systems Biology

Data

Information

Knowledge

SystemsBiology

Bringing data, information and knowledge towards application

BioExpert

BioExpert implements knowledge bases

Annu. Rev. Biochem. 2006. 75:295–332

Experts already represent their knowledge…

Human readable, not computer processable

Fatty acid metabolism from KEGG: many facts but little insight

Oxidation

hydration

dehydrogenation

Thiolysis

Peroxisomal beta-oxidation ceases at Octanoyl CoA

Activation

mitochondrion

Peroxisome

Different substrates usedifferent enzymes

Background knowledge: what is Hydration?

Knowledge Base

BioExpertInformation Management

Framework

BioExpert project overview

KB may contain any type of biomedicalknowledge; not restricted to pathways

Peroxisome(PxKB)

BioExpertFramework

BioExpert knowledge bases

Polyphenoldegradation

(PpDKB)

YeastGlycolysis

(YgKB)

MetabolicSyndrome(MeSKB)

NCSB-NBIC (open position) Systems BiologyStart a.s.a.p

YgKB: Prof. dr. B. Teusink (Molecular Cell Physiology, VU)MeSKB: Dr. K. Willems van Dijk (Human and Clinical Genetics, LUMC) Jeroen Jeneson (Biomedical NMR, TUe), Roeland Merks (CWI), Hans van Beek (VU)

The Peroxisome Knowledge base (PxKB)

peroxisome

What are peroxisomes?

FunctionFatty acid β-oxidationBile acid formationFatty acid α-oxidationPlasmalogen biosynthesisCholesterol biosynthesis?Glyoxylate breakdownother

DisordersPeroxisome biogenesis disorders

Zellweger syndrome

Single peroxisomal enzyme deficiencies

X-linked adrenoleukodystrophy ALDPAcyl-CoA oxidase deficiency ACOX1D-bifunctional protein deficiency D-BP2-methylacyl-CoA racemase deficiency AMACRRhizomelic chondrodysplasia punctata type 2

DHAPATRhizomelic chondrodysplasia punctata type 3

ADHAPSRefsum's disease PhyHHyperoxaluria type 1 AGTGlutaric acidemia type 3 ???(Mevalonate kinase deficiency?) MVK Acatalasaemia CAT Mulibrey nanism MUL

The challenges

• Knowledge representation

• Knowledge presentation

• Knowledge acquisition

• Knowledge navigation and querying

• Knowledge application

Knowledge representation

• Semantic Web Initiative: – represent web content in a form that is more easily

machine-processable – to use techniques to take advantage of these

representations

• Semantic Web Aim: – more advanced knowledge management systems

Antoniou, Van Harmelen. A Semantic Web Primer, 2nd edition. Cambride: The MIT Press, 2008.

Semantic Web technologyRDF Resource Description Framework

Provides foundation for representing and processing metadata

RDF Schema Primitive ontology language

SKOS Simple Knowledge Organization SystemAn ontology for expressing the basic

structure and content of e.g., controlled vocabularies.

OWL Web Ontology LanguageProposed standard for web-ontologies.

Allows to describe the semantics of knowledge in a machine-

accessible way

SPARQL RDF query language

Foundation: RDF triple

Graphic representation of triple:

Subject Objectproperty

Mitochondrion Cellpart-of

The challenges

• Knowledge representation

• Knowledge presentation

• Knowledge acquisition

• Knowledge navigation and querying

• Knowledge application

Knowledge presentation: Concept Maps

• Intuitive– Non-technical– “Easy” to make

• Clear– Graphical

presentation

• Concise– Focus / context

A.J. Canas et al., “Concept maps: Integrating knowledge andinformation visualization,” in , vol. 3426, Lecture Notes in Computer Science (BERLIN: Springer-Verlag Berlin, 2005), 205-219.

Did you recognize the RDF triples?

Semantic typing (RDFS / OWL)

The challenges

• Knowledge representation

• Knowledge presentation

• Knowledge acquisition

• Knowledge navigation and querying

• Knowledge application

The challenges

• Knowledge representation

• Knowledge presentation

• Knowledge acquisition

• Knowledge navigation and querying

• Knowledge application

Application of KB in systems biology

• Annotation of biological system– Detailed and curated– Linked to external data(bases)– Possibly embedded in larger context (not part of modeling)– Facilitates mathematicians to correctly define model

• Annotation of mathematical models– Allows biologists to verify model

• Validation of results– Are results consistent with available knowledge

• Generation of new hypotheses

(How to) connect BioExpert to.....

• SBML

• CellML

• MIRIAM: Minimal Information Requested in the Annotation of Biochemical Models

• Systems Biology Ontology

• TEDDY: Terminology for the Description of Dynamics

• MIASE: Minimum Information About a Simulation Experiment

• KiSAO: Kinetic Algorithm Ontology

• SysMo DB / Taverna workflows / etc

The BioExpert Team

Dr. Andrew GibsonProject leader

Dr. Gerbert Jansen

Serge Barth, MSc

Joris Scharp

PhD position(translational medicine)

PhD positionGrey statistical models

PositionNCSB-NBICsystems biology

Paul van Hooft

Wiebe Posthuma