|Monday 27 January 2020|
|Events for day: Thursday 05 December 2019|
| 10:00 - 11:00 Weekly Seminar|
Bayesian inference of biological networks
Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. In this talk, after giving an introduc ...