Stefan Kesselheim

This study uses GWAS and genomic prediction to identify SNPs influencing photosynthetic efficiency in Arabidopsis under different nighttime temperatures, showing polygenic control and improved prediction accuracy.

This paper introduces a computational framework using nanopore sequencing and deep learning to infer microbial viability from raw signal data, showing high accuracy in controlled and real-world applications.

The paper introduces MISATO, a dataset combining quantum mechanics properties and molecular dynamics simulations of protein-ligand complexes to support structure-based drug discovery.