David J. Degnan

This paper uses spatial microproteomics to characterize the proteomic landscape of Bacillus subtilis biofilms, identifying subpopulations through proteoform analysis.

This paper develops a spatial proteomics workflow to identify and map proteoforms in human kidney tissue, revealing spatially distinct proteomic profiles between glomeruli and tubules.

The paper introduces nanoSPLITS, a platform for simultaneous transcriptome and proteome profiling of single cells, and demonstrates its application in cell cycle regulation and cell type identification.

The paper presents best practices for analyzing and integrating data from wearable silicone wristbands to enable meta-analyses and broader community research.

This study evaluates and refines assumptions in retention index scores for GC-MS metabolite identification to improve accuracy and reduce manual verification.

This paper improves false discovery rate estimation in GC-MS metabolomics by extending Gaussian mixture models to incorporate similarity scores and experimental data.