David D. Shteynberg

Carafe generates high-quality in silico spectral libraries for DIA proteomics by training deep learning models directly on DIA data, improving fragment ion intensity prediction and peptide detection.

The paper audits error control in twelve crosslinking mass spectrometry pipelines using ground-truth designs, finding some pipelines exceed false discovery rates by up to 29-fold.

PTMProphet provides localization confidence for post-translational modifications in proteomics data, improving accuracy for downstream analysis.