Knowledge about the Michaelis constant KM and the turnover number kcat for enzyme-catalyzed reactions is required for advanced models of cellular metabolis. However, since the experimental measurement of kcat and KM is difficult and time consuming, no experimental data exists for many relevant enzymes. To approach this problem, I am trying to predict these values using methods from Machine and Deep Learning. To train different models, I use information about enzyme structures, substrates, assay conditions, and metabolic network properties.
I was involved in organization and exercise groups for students in the following lectures:
- "Algorithmen und Datenstrukturen" (winter Semester 2019/2020)
- "Rechnerarchitektur" (sommer semester 2019)