Marcus Weber

This paper presents an evolutionary algorithm framework combining generative AI and virtual screening to efficiently explore large chemical spaces and identify novel drug candidates.

The paper introduces a domain decomposition approach to efficiently compute Markov State Models for stochastic gene regulatory networks with uncertainty quantification.

The paper develops a stochastic model of GPCR function in inflamed environments and validates it with experimental data, showing that low pH has a greater impact on GPCR behavior than radicals.