Michael O. Krauthammer

Early antifungal resistance prediction based on MALDI-TOF mass spectrometry and machine learning

The paper develops a machine learning pipeline using MALDI-TOF mass spectrometry data to predict antifungal resistance and identify biomarkers, achieving high performance across multiple yeast species and drug combinations.

Uncovering Cas9 PAM diversity through metagenomic mining and machine learning

The paper develops CRISPR-PAMdb and CICERO to uncover PAM diversity in Cas9 proteins, enabling better CRISPR tool design.

Predicting prime editing efficiency across diverse edit types and chromatin contexts with machine learning

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens

This paper develops BE-DICT, a deep learning model trained on high-throughput screens to predict base editing outcomes with high accuracy.