Statistical and numerical aspects of cryogenic electron microscopy

• Applicant: Dr. Gilles Mordant
• Subject Area: Statistics and Econometrics ; Structural Biology
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 563103368

The objective of this project is to advance the statistical and computational methods for cryogenic electron microscopy. In particular, we are interested in improving the output of molecular dynamic simulations or machine learning methods by enriching them on the basis of actual data. Merging these data sources raises new statistical and numerical challenges, such as quantifying the improvements made to the molecular Hamiltonian or providing theoretical guarantees on the reconstructed conformational landscape, i.e., on the estimated space of potential conformations of a molecule of interest.

• DFG Programme: Research Grants
• International Connection: USA
• Cooperation Partners: Dr. Pilar Cossio; Professor Dr. Roy Lederman