Our proposal "Inferring Continuous-Time Reaction Models from Time-Series Data (INCRE)", submitted jointly with François Fages (Inria), has been approved by the DFG and ANR.
Machine learning methods are transforming many areas of science and open up new opportunities for developing quantitative simulation models. A particularly promising direction, and the focus of INCRE, is inferring mechanistic simulation models directly from time-series data. In particular, the project will develop new methods to infer chemical reaction networks, a standard modeling formalism in systems biology.
We thank the reviewers, the DFG and the ANR for their time and the trust they have placed in us. We look forward to INCRE bringing together researchers from Paris and Rostock.