Concur 2004
Mon 30 Aug 2004 11:21 BST
I’m sitting in the foyer of the Royal Society in London. This is the venue for Concur 2004, a conference on Concurrency Theory. I’m just attending a couple of the workshops — specifically BioConcur ‘04 and, next Saturday, AVoCS ‘04.
BioConcur
So far there’s been a talk by Corrado Priami giving an overview of the application of concurrent languages (such as the π-calculus) to the field of Systems Biology.
One success-story so far is that of a study that was made of inflammatory processes in Multiple Sclerosis-affected brain blood vessels. A π-based model was constructed, and simulations of the model were observed. The graphs of the simulations led to the formation of a hypothesis, previously unstudied, relating the number of rolling lymphocytes to blood vessel diameter. Later investigation in mice demonstrated the validity of the hypothesis.
I made a few random notes:
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How does π improve over CCS with regard to cost? Why are names interesting from a cost point-of-view in biological models?
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ODEs (Ordinary Differential Equations) are noncompositional; π is linguistically compositional; it seems to me that these biological models are partly compositional, partly noncompositional, because of the need for encoding of biochemical behaviours (?).
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The table Priami presented relating π to biological systems:
Molecule Process Interaction Capability Channel Interaction Communication Modification State and/or channel change Compartments are modelled with restriction, in the absence of ambients or ambient-like structures. This is an acknowledged problem with using π for these models.
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The π-based model treats a molecule as a black box with a number of interaction capabilities, each of which has a defined syntactic and behavioural specification for its interactions.
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The exponential distribution used for selecting the next action gives a memoryless property to the system
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In the stochastic π calculus, there is a forced zero collision property — the system excludes the possibility of a collision in competing for resources. This keeps the world nice and deterministic…
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There are standard tools for performance analysis of Continuous Time Markov Chains (link).
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RCCS is another way of modelling these systems - the R stands for “reversible”!
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Model checking is complicated by the stochasticness of the system; model checkers usually like a deterministic universe…
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What kinds of equivalence between processes are biologically interesting?
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Inductive Logic Programming is another alternative approach.