Flowering time regulation that has been widely examined in the plant model species – Arabidopsis thaliana, has a large complex network system. A quantitative approach provides to understand the numerical amount of genes impact strength in each other. Therefore, a quantitative and dynamic modelling of this network based on a system of differential equations is required.
Research interest;
Dynamic modelling of the Arabidopsis thaliana flowering time gene regulation.
An efficient set of parameters for the dynamics of Arabidopsis thaliana flowering time GRN by using an ODE identification (ODEion) method with (no-delay and delay), and compared with the polynomial fitting experimental expression time-course data.
Stability analysis of simplified model.
Analytical and numerical solutions of the dynamic model.
Supervisors
- Prof. Maia Angelova
- Dr. Benoit Huard
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