Chris Hsu

Bromo, a pairwise transformer, ranks a protein's peptide precursors by expected mass spectrometry response, beating XGBoost, PREGO and PeptideRanger on held-out yeast data, and can be fine-tuned per instrument.

This study revisits resonance-excitation collision-induced dissociation (reCID) for DIA proteomics, showing it can achieve performance comparable to HCD with optimized settings and libraries.

DNA O-MAP identifies molecular neighborhoods around specific genomic loci using programmable probes and proteomics.

Carafe2 generates high-quality in silico spectral libraries for timsTOF DIA proteomics by fine-tuning deep learning models on DIA data, outperforming DDA-trained models in multiple applications.

The paper develops scalable targeted proteomics assays using the Stellar mass spectrometer for analyzing biofluids, demonstrating high sensitivity and multiplexing capabilities.

The paper improves Casanovo, a deep learning de novo peptidesequencer, by enhancing interpretability, generalizing its use in database search, speeding up performance, and adding tools for adoption and result interpretation.

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.

This paper evaluates a prototype Orbitrap Astral Zoom mass spectrometer for quantitative proteomics, showing improved performance in ion detection and quantitative precision compared to the standard Orbitrap Astral MS.

The paper analyzes rare coding variants in smoking and drinking behavior using exome chip data, finding that they contribute to phenotypic variation but require larger samples for individual variant associations.