Moritz Ertelt

The paper validates and analyzes 12,000 AI-designed CAR-T binders from a global competition, identifying successful designs and factors improving their performance.

The paper introduces KlebPhaCol, a resource containing 53 phages and 74 Klebsiella isolates, including a novel gut phage order, to advance understanding of Klebsiella-phage interactions.

This study compares self-supervised ML methods with biophysical approaches in protein design, finding ML improves sampling but not scoring of high-fitness variants.

This paper introduces HyperMPNN, a deep learning model trained on hyperthermophile proteins to design highly thermostable proteins, achieving stability up to 95°C.