Julia A. Bubis

This study compares the performance of Orbitrap Astral and Eclipse mass spectrometers in CLMS, finding the Astral provides higher sensitivity and more unique residue pairs.

This paper introduces an ultrafast metaproteomics method using Orbitrap MS to rapidly and accurately assess microbial identity and functional activity without peptide fragmentation.

This paper introduces a high-throughput single-cell proteomics workflow achieving 5300 protein groups per cell with high accuracy, enabling the study of cellular heterogeneity and lineage differentiation.

The paper reanalyzes proteomic datasets to identify ADAR-mediated RNA editing events and finds 18 core recoded protein sites across human tissues.

IQMMA improves protein quantitation in DDA proteomics by integrating multiple feature detection algorithms to extract more accurate MS1 intensities.

This study compares DirectMS1Quant, an MS1-only quantitation method, with MS/MS-based methods like LFQ, TMT, and DIA, showing comparable efficiency despite shorter runtime.

The paper evaluates consensus spectrum generation methods in proteomics, finding BEST and BIN to be the most reliable for peptide identification.

AA_stat improves interpretation of open search results in proteomics by adding features for mass shift localization, modification inference, and calibration.

The paper improves the DirectMS1 proteomics method using machine learning to identify over 2000 proteins in 5 minutes with 1% FDR.