Tata Institute of Fundamental Research
Model Reduction in Systems Biology
Seminar
Speaker:
Carsten Wiuf (University of Copenhegan
Department of Mathematical Sciences
Uiversitersparken 5
DK-2100 Copenhagen
Denmark)
Organiser:
Manoj Gopalkrishnan
Date:
Wednesday, 6 Nov 2013, 16:00 to 17:00
Venue:
AG-69
(Scan to add to calendar)
Abstract:
Abstract: Models based on Ordinary Differential Equations (ODEs) or their stochastic counterparts are routinely applied in systems biology to understand, analyze and predict properties and behaviour of biomolecular dynamical systems, such as enzymatic networks. However, the system's properties and behaviour depend strongly on the modeling equations and the assumptions we make about the system. How robust are predictions with respect to the assumptions? What can we say about the mathematical relationship between different models of the same biological system?
In recent years, model reduction -- how do we simplify a complex model without loosing essential properties of the model -- has been a topic in stochastic and deterministic reaction network theory. In this talk, I will discuss model reduction and some recent results on model reduction, based on deterministic as well as stochastic systems, at steady state, as well as out of steady state.
| Speaker: | Carsten Wiuf (University of Copenhegan Department of Mathematical Sciences Uiversitersparken 5 DK-2100 Copenhagen Denmark) |
| Organiser: | Manoj Gopalkrishnan |
| Date: | Wednesday, 6 Nov 2013, 16:00 to 17:00 |
| Venue: | AG-69 |
(Scan to add to calendar)
Abstract:
Abstract: Models based on Ordinary Differential Equations (ODEs) or their stochastic counterparts are routinely applied in systems biology to understand, analyze and predict properties and behaviour of biomolecular dynamical systems, such as enzymatic networks. However, the system's properties and behaviour depend strongly on the modeling equations and the assumptions we make about the system. How robust are predictions with respect to the assumptions? What can we say about the mathematical relationship between different models of the same biological system?
In recent years, model reduction -- how do we simplify a complex model without loosing essential properties of the model -- has been a topic in stochastic and deterministic reaction network theory. In this talk, I will discuss model reduction and some recent results on model reduction, based on deterministic as well as stochastic systems, at steady state, as well as out of steady state.
In recent years, model reduction -- how do we simplify a complex model without loosing essential properties of the model -- has been a topic in stochastic and deterministic reaction network theory. In this talk, I will discuss model reduction and some recent results on model reduction, based on deterministic as well as stochastic systems, at steady state, as well as out of steady state.