Christof Schütte

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 Chimeric U-Net, an invertible decoder U-Net architecture that enhances explainability in semantic segmentation without compromising performance.

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.

This paper shows that inferring gene regulatory networks from scRNA-seq data requires considering higher-order statistical moments and highlights challenges in preprocessing and feature extraction.

The paper introduces a network-based feature selection framework for lung adenocarcinoma prognosis, achieving high prediction performance using EMT-related signatures.