From 2011 Feb the 14th to Feb. the 18th — CS department of ENS Lyon.
The goal of this course is to give an overview on rule-based modelling.
Rule-based approaches (as in our own Kappa, or BNGL, or many other
propositions allowing the consideration of “reaction classes”) offer
some means to capture combinatorial molecular interactions as we find
them in biological subcellular systems. This is trying to fill a need
that seems ever more pressing – as molecular biology uncovers more
amazing combinational structures. In so doing we get a more physically
realistic, less parameter-hungry, and more structured approach to the
modeling/programming of combinatorial molecular networks.
We will explain the approach through numerous motivating examples. We
will also reenact various methods commonly employed in the
verification and analysis of concurrent systems to support our
approach with analytic tools, such as: static analysis (qualitative
and quantitative) for reachability questions and for the reduction of
dynamical systems, causality analysis (including methods for the
compression of partial time traces), and more specific “termination”
methods using local energy functionals to guarantee thermodynamical
The intended audience is students and staff in theoretical computer
science/concurrency theory, computational biologists with an interest
in modelling techniques, statistical physicists/applied mathematicians
with an interest in biomodelling.
Pedagogical materials will be in English.
Lectures will be given in English.
- 10h00-12h00 : Basics of modeling (V. Danos)
- 14h00-17h00 : Basics of modeling (V. Danos)
- 10h00-12h00 : Introduction to kappa (J. Krivine)
- 14h00-17h00 : Dynamics (J. Krivine)
- 10h00-12h00 : Static analysis (J. Feret)
- 14h00-17h00 : Model reduction (J. Feret)
- 10h00-12h00 : Model reduction (J. Feret)
- 14h00-17h00 : Modeling session: epigenetics (J. Krivine)
- 10h00-12h00 : Energy and syntax (V. Danos)
- 14h00-17h00 : Extensions
Basics of modeling : Petri-Nets, mass action law, detection of equilibriums and steady states, thermodynamic limit (Kurz theorem).
Introduction to kappa : Notion of model in biology, syntax and operational semantics.
Dynamics : Gillespie’s algorithm, scalability issue, causality.
Static analysis : Qualitative analysis, reachability (completeness result), species enumeration algorithm.
Model reduction : Information flow, ODE semantics, stochastic semantics.
Energy and syntax : Information flow, ODE semantics, stochastic semantics.
Extensions : Compartments, agent variants,diffusion.
This course requires no prelimary knowledge.
The fundamental notions which will be used in this course will be properly introduced.
- V. Danos, C. Laneve. Formal Molecular Biology. In Theoretical Computer Science 325, 2004.
- V. Danos, J. Feret, W. Fontana, R. Harmer,& J. Krivine. Rule-based modelling of cellular signalling. Invited in International Conference on Concurrency Theory(CONCUR 2007), number 4703 in Lecture Notes in Computer Science. 2007, © Springer.
- J. Krivine, V. Danos, A. Benecke. Modelling epigenetic information maintenance: a Kappa tutorial Invited tutorial in Computer Aided Verification(CAV 2009), number 5643 in Lectures Notes in Computer Science. 2009, © Springer.
- V. Danos, J. Feret, W. Fontana,& J. Krivine. Scalable modelling of biological pathways. Invited in Asian Symposium on Programming Systems(APLAS 2007), number 4807 in Lecture Notes in Computer Science. 2007, © Springer.
- V. Danos, J. Feret, W. Fontana, R. Harmer,& Jean Krivine. Abstracting the differential semantics of rule-based models: exact and automated model reduction. Invited in Logic in Computer Science (LICS 2010). 2010, © IEEE Computer Society.
- V. Danos, N. Oury. Energy and Termination. In Developments in Computational Models 2010, Causality, Computation, and Physics (DCM 2010). 2010, © Electronic Proceedings in Theoretical Computer Science.