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Compositional Stochastic Models of Gene Networks
Compositional Stochastic Models of Gene Networks

This project develops an approach for constructing dynamic models of gene regulatory networks from simple computational elements. While traditional approaches require fixing the network topology beforehand, the modularity of our approach allows us to pass easily from a basic first-level description of a biological system to more refined models. As an illustrative application we study the design principles for constructing robust, stochastic cellular clocks from genetic building blocks.

The project aims to uncover some of the molecular mechanisms that underpin the design of reliable oscillators from genetic building blocks. One factor that comes into play is the level of cooperativity between proteins, where proteins that form polymers before repressing a gene tend to produce more robust oscillators, which are less sensitive to noise in gene transcription. By piecing together a collection of basic principles, we can begin to understand the rules which govern the behaviour of more complex oscillatory systems.