Speaker |
Robert Stojnic |
|---|---|
Affiliation |
Cambridge Systems Biology Centre |
Date |
Friday, 07 March 2014 |
Time |
13:00-14:00 |
Location |
Zoom |
Link |
Malet Place Engineering 1.03 |
Event series |
DeepMind/ELLIS CSML Seminar Series |
Abstract |
The assembly of cellular components has been traditionally modelled using differential equations. In this work I will present a new formalism that yields a model similar to Bayesian Networks where every node represents one molecule. The intuition behind the model can be captured with an analogy to LEGO building blocks where blocks (=molecules) are successively added to create the final molecular structure. I will show that the structure can be reverse-engineered from measurements of molecular abundance under perturbation. I will discuss the Bayesian approach to structure inference, and derive an efficient maximum a-posteriori inference scheme with uniform priors. I will discuss how the choice of prior has crucial influence on the success of inference. |
Biography |