Multiscale Modelling
Project Fallot
Tariq Abdulla
December 2009
Outline
• Information Modelling – Ontologies, XML and
databases
• Petri nets – graph based representation of
networks and pathways
• Network Analysis – network type, motifs
• Integration of models
Ontologies
1. Provide a common, structured vocabulary, in order to
overcome confusion in terminology.
2. Facilitate the integration and querying of
heterogeneous datasets (and, increasingly, models).
Gene Ontology
1. Collaboration between model organism databases –
thus inherently cross-species
2. Reference ontology – for more specific annotation, we
may develop application ontologies, that reference GO
and other reference ontologies
3. Split into 3 seperate ontologies: Biological Process,
Cellular Component and Molecular Function
Gene Ontology: AmiGO
Gene Ontology: AmiGO
Rat Genome Database
Nkx2.5
Rat Genome Database
Jagged1
(Horridge et al. 2009)
Properties
Functional
Inverse Functional
Symmetric
Transitive
Reflexive
Irreflexive
Properties
Automatic Classification
Automatic Classification
Petri Nets
t2
p1
t1
p3
p2
t3
3
place
transition
arc
inhibitory arc
token
p4
vmax = Kcat[E]
(Gilbert, et al. 2006)
SBML – Enzyme Reaction
KEGG Representation
Is this straightforward?
(Heiner, Koch and Will 2004)
(Heiner, Koch and Will 2004)
Pathways: structural differences
Metabolic Networks
(Breitling, et al. 2008)
Signal Transduction Networks
Phosphorylation
Kinase
Signalling
Protein
Phosphorylated
Form
Phosphotase
Notch Signalling
(Artavanis-Tsakonas, Rand and Lake 1999)
Hybrid Petri Nets
• Places and Transitions can be either discrete
or continuous
HFPN: Notch Signalling
HFPN: Notch Signalling
XML Representation of HFPN
P1
m1
P2
T1
1
m1/2
m2
m1/2.5
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE hybridFunctionalPetriNet SYSTEM "SampleHFPNet.dtd">
<HFPN>
<place id="P1" type="continuos" variableName="m1"/>
<place id="P2" type="continuos" variableName="m2"/>
<transition id="T1" speedFunction="m1/2.5" type="continuos"/>
<arc from="P1" to="T1" type="normal" weight="1"/>
<arc from="T1" to="P2" type="normal" weight="m1/2"/>
</HFPN>
How Can we understand this?
Network Analysis!
Signalling Pathways are robust because:
• They are small world, scale free networks
Power Law
Distribution:
P(k)∼k−γ
Signalling Pathways are robust because:
• There are redundant pathways, feedback
loops, and combinatorial complex
• Cross-talk between pathways provide
additional sites to regulate signalling
Network Motifs
Network Motifs
(Prill, Iglesias and Levchenko 2005)
Model Checking
• Liveness
• Reachability
• P and T invariants
Mining Pathway Information
• Pathway databases are either created by
curators, or through text mining of the
literature
• Curated databases tend to be higher quality,
but the breadth may be narrower
Levels of Abstraction
Why model?
• Generate new insights
• Make testable predictions
• Test conditions that may be difficult/impossible to
study in vitro / in vivo
• Rule out particular explanations for an experimental
observation
• Help identify what is right/wrong with an hypothesis
Analysis and Interpretation
• Validation: do the model results match
experimental data?
• Prediction:
– Sensitivity analysis
– Knockout experiments
Information Management
• Identify building blocks / submodels
• Database
– Models, model components
– Behaviours
– Properties
• Component reuse
• Version control
• Model checking
– Maintaining temporal-logical properties
A Proposition:
• Find out the expression of Delta and Notch in
the precursor cells of the Heart fields at an
early stage
• Simulate to find if the patterning corresponds
to what is expected
Conclusion
• By encoding models, literature and experimental
results in XML, and storing them in web-accessible
databases, intermediated by ontologies, we
facilitate more holistic approaches.
• A range of modelling are appropriate to different
levels of scale
• In the places where these can begin to be
integrated, there is insight to be gained in silico
References
Horridge, Matthew, Simon Jupp, Georgina Moulton, Alan Rector, Robert Stevens, and Chris Wroe.
"A Practical Guide To Building OWL Ontologies Using Protégé 4." CO-ODE. October 16, 2007.
http://www.co-ode.org/resources/tutorials/ProtegeOWLTutorial.pdf
Gilbert, David, et al. "Computational methodologies for modelling, analysis and simulation of signalling
networks." Breifings in Bioinformatics 7, no. 4 (2006): 339-353.
Heiner, Monika, Ina Koch, and Jürgen Will. "Model validation of biological pathways using Petri nets—
demonstrated for apoptosis." Biosystems 75 (2004): 15-28.
Breitling, Rainer, David Gilbert, Monika Heiner, and Richard Orton. "A structured approach for the
engineering of biochemical network models, illustrated for signaling pathways." Briefings in Bioinformatics
9, no. 5 (2008): 404-421.
Matsuno, Hiroshi, Ryutaro Murakami, Rie Yamane, Naoyuki Yamasaki, Sachie Fujita, and Haruka Yoshimori.
"Boundary Formation by Notch Signalling in Drosophila Multicellular Systems: Experimental Observations
and Gene Network Modeling by Genomic Object Net." Pacific Symposium on Biocomputing. Kauai, Hawaii:
World Scientific, 2003. 152-163.
Artavanis-Tsakonas, Spyros, Matthew D. Rand, and Robert J. Lake. "Notch Signaling: Cell Fate Control and
Signal Integration in Development." Science 284 (1999): 770-776.
Prill, Rober J., Pablo A. Iglesias, and Andre Levchenko. "Dynamic Properties of Network Motifs Contribute
to Biological Network Organization." PLOS Biology 3, no. 11 (2005): 1881-1892.
Further Reading
Fisher, Steven A., Lowell B. Langille, and Deepak Srivastava. "Apoptosis During Cardiovascular
Development." Circulation Research, 2000: 856-864.
Gittenberger-de Groot, A. C., and R. E. Poelmann. "A Subpopulation of Apoptosis-Prone Cardiac
Neural Crest Cells Targets to the Venous Pole: Multiple Functions in Heart Development?"
Developmental Biology, 1999: 271-286.
Barabási, Albert-László, and Zoltán N. Oltvai. "Network Biology: Understanding the Cell’s Functional
Organization." Nature Reviews: Genetics, 2004: 101-113.
Rector, Alan, Jeremy Rogers, and Thomas Bittner. "Granularity scale and collectivity: when size does
and does not matter." Journal of Biomedical Informatics, no. 39 (2006): 333-349.
Fisher, Jasmin, and Thomas A Henzinger. "Executable cell biology." NATURE BIOTECHNOLOGY 25,
no. 11 (2007): 1239-1249.
Novere, Nicholas Le, Melanie Courtot, and Camille Laibe. "Adding Semantics in Kinetics Models of
Biochemical Pathways." 2nd International ESCEC Symposium on Experimental Standard Conditions
on Enzyme Characterizations. Rhein: Beilstein Institut, 2006. 137-153.
Niessen, Kyle, and Aly Karsan. "Notch Signalling in Cardiac Development." Circulation Research, 2008:
1169-1181.
Walker D C, Southgate J S, Hill G, Holcombe M, Hose D R, Wood S M, MacNeil S and Smallwood R H
(2004) The Epitheliome: modelling the social behaviour of cells. BioSystems 76:89-100