ICE-TCS Lectures Series - Juris Viksna - Dependence of dynamic properties of gene interaction networks on the network topology and parameter values


On Friday, October 29th, Juris Viksna (University of Latvia, Department of Computer Science) delivers an ICE-TCS seminar. The talk, which is entitled Dependence of dynamic properties of gene interaction networks on the network topology and parameter values, will be held at 2pm in room M1.05 at Reykjavik University (Menntavegur 1).

The lecture is open to everyone.


When describing gene networks one should distinguish between: 1) network topology - a  diagram showing which protein interact with what other elements of the network influencing the expression of which other proteins, and 2)numerical parameters characterizing the strength of such interaction and their  quantitative effects on expression.

Assuming that it is possible to separate between the topology and quantitative parameters  in the model, we can study to what extent the qualitative behaviour of the system depends on the topological structure of the network, and to what extent the exact quantitative values (relative or absolute) of the parameters are crucial.

To describe gene networks we propose a formalism based on hybrid systems, which provides a direct way of modelling both discrete events, such as protein binding on one hand, and continuous behaviour, such as protein concentration changes on the other hand. Hybrid systems also provide a natural separation between the description of the network topology and quantitative model parameters.

We apply our model and analysis methods to a well studied gene network of lambda phage. Lambda phage has too well known qualitatively different behaviours - lysis and lysogeny. We show that our model has an attractor structure that corresponds well to these two behaviours and is largely independent of the concrete parameter values. More concretely, the model exhibits six possible behaviours, two of which corresponds to lysis, one to lysogeny, and the remaining ones to altered 'lysis' and 'lysogeny'-like behaviours. Whether the system will exhibit the normal or altered lysis/lysogeny behaviour depends on the relative ordering of some of the parameter values. This imposes constraints on the relative order of parameter values if our model behaviour is to correspondto the real world observations. We also identify a particular parameter in the model, whose exact quantitative value (in relationship to other parameter values) affects the model behaviour substantially.