Daniel Paul Zolg

This paper introduces Prosit-PTM, a deep learning model for PTM discovery that improves zero-shot prediction using a synthetic dataset and chemically-informed encoding.

CHIMERYS deconvolves chimeric spectra in proteomic data, enabling unified analysis across DDA, DIA, and PRM experiments by accurately identifying and quantifying multiple peptides per spectrum.

The paper creates a proteome and transcriptome atlas of 29 human tissues, revealing differences in mRNA-protein abundance and challenges in proteogenomics.