Paris/Stochastic models

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Why stochastic models?

We chose to make stochastic because of the lack of knowledge (No kinetic constant or association constant aviable) . With this kind of model we just have to infer rules and chose a probability of application for it. We just need an order of time for a rule to occur (Cell division time >> gene expression time), with this we can estimate the probability.

What have we done

We work on two kinds of stochastic models, one at the part scale the other at the device scale. Why ? because we try to follow the spirit ofiGEM : we build a model for a part A (promoter) with a lot of rules (association/dissociation of the inhibitor/activator and so on) and a second part B (reporter) with another set of rules. Now we want to make a model for the device promoter::reporter we can make a huge model with all the rules... Or as we known we have models for the parts that work we can put a black box on the device and just create a set of global rules and work at the device scale.

Which tool

All the stochastic modeling have been made with MGS, it is a research project in the IBISC (Laboratory for Computer Science, Integrativce Biology and Complex Systems) of the University of Evry, CNRS and Genopole. (http://mgs.ibisc.univ-evry.fr)

Simple automaton

A model focused on the diffusion of DAP and the differentiation between germinal and somatic cells

Complex automaton

A model focused on the evolution of the bacteria putting black box on the process describe by the simple automaton