معرفی
Gergely Katona is a Professor at the Department of Chemistry & Molecular Biology, University of Gothenburg. His research focuses on structural biology, particularly crystallographic investigations of protein dynamics, and he integrates artificial intelligence (AI) into biophysical data analysis.
- Chairman of the Chemistry Program Committee
- Main examiner for Chemistry programs
- Teaches courses like KEM350 and KEM360
Katona's research explores enzyme mechanisms using X-ray techniques and AI, with applications in cancer biology and autoimmune diseases. He pioneered methods to study reacting enzymes via chemical triggering and Bayesian analysis of MST/BLI/NMR data.
His recent work combines structural biology with machine learning to predict protein interactions and mutation fitness, as seen in his Survivin studies. He holds a patent for peptide-targeting technology.
Katona supervises doctoral, master, and bachelor students, emphasizing method development and independent research skills. He reviews applications for EMBL beamlines and the iNEXT network.
