prof. dr. antoine van kampen bioinformatics laboratory academic medical center (amc) biosystems data...
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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
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
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)
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.
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