Paul A. Rudnick

The paper presents two large-scale proteomics datasets from mice exposed to varying X-ray doses and time points, enabling biomarker discovery and machine learning applications for radiation exposure assessment.

This paper introduces a transformer-based model called Cascadia for de novo sequencing of data-independent acquisition mass spectrometry data, achieving state-of-the-art performance.