Ariana E. Shannon

This study introduces MAP-MS, a method to improve proteomic dynamic range using Orbitrap mass spectrometers without hardware or software changes, achieving nearly 2x dynamic range with minimal impact.

The paper develops a workflow for targeted proteomics using a hybrid quadrupole-linear ion trap instrument, demonstrating consistent quantification without high-mass accuracy.

The paper introduces Chronologer, a deep learning tool for accurate peptide retention time prediction, outperforming existing methods by leveraging harmonized datasets of post-translational modifications.

Scribe improves library searching for DDA experiments by predicting fragmentation and retention times for all peptides, outperforming traditional database searching in sensitivity and precision.