Shubham Gupta

STRIDE improves phosphopeptide quantification by reducing false negatives and enhancing consistent peak assignment across DIA-MS runs.

DreamDIAlignR improves DIA proteomics analysis by integrating cross-run peptide data with deep learning and FDR control, increasing detected quantitatively changing proteins by 25.6% on a benchmark dataset.

DIAlignR improves quantification consistency in DIA proteomics data across multiple LC-MS/MS instruments, reducing identification errors and increasing significant protein detection.

The paper describes an open-source workflow for peptide-level quantitation from DIA/SWATH-MS data using Docker-based containerization.

DIAproteomics is an automated pipeline for analyzing DIA proteomics and peptidomics data, offering tools for spectral library generation, alignment, and statistical analysis.

DrawAlignR provides interactive visualization of chromatogram alignments for DIA/SWATH data and includes a faster C++ alignment algorithm.

The paper identifies three lncRNAs and develops a nomogram model to improve diagnosis of pulmonary tuberculosis in patients without microbiologic evidence.

DIAlignR improves retention time alignment in SWATH-MS data by aligning raw MS2 chromatograms, outperforming existing methods and reducing alignment error significantly.