February 2022 CDT in Maths of Random Systems Workshop
CLORE LECTURE THEATRE – HUXLEY BUILDING, IMPERIAL COLLEGE LONDON
For remote access please contact Lydia Noa
| 12.40 – 13.15 | Arrival and Coffee |
|
13.20 – 13.50  |
Closed-loop Nash competition for liquidity |
|
13.50 – 14.20  |
Uncovering Genealogies of Populations with Local Density Regulation |
|
14.25 - 15:10 
|
Path integral approaches to model reduction in biochemical network |
Abstract (Barbara Bravi)
Both fundamental and practical limitations have emerged in quantitative approaches to studying biochemical networks, such as protein-protein interaction networks, because of the extremely large number of reacting species, as well as the presence of nonlinearities and stochastic terms in the dynamics. The comparison itself with experimental results can be subject to an overall uncertainty due to missing variables and low-resolution measurements. In such networks, it is hence often convenient to select for the analysis a ‘subnetwork’, i.e. , a subset of nodes of interest, either because they are better characterized from the theoretical point of view or because they are the only ones to be observed experimentally. The subnetwork will be embedded in a larger network (the `environment'), which is unobserved. In this talk, I will discuss a framework, based on a path integral formulation of the dynamics, to work out a reduced subnetwork description, given by equations of motion that describe only the subnetwork while retaining dynamical effects from the environment in the form of time-delayed interactions (memories) and a coloured noise. I will show how the systematic inclusion of these terms ensures accurate predictions for the subnetwork dynamics in an example of protein-protein interaction network.
