Mikhail V. Gorshkov

The paper introduces msallsearchpy, a search engine for high-flow quantitative LC-MS proteomics, showing improved identification and quantification performance over existing methods.

This study investigates the mechanism of action of a Pt(IV) complex with lonidamine ligands using chemical proteomics in ovarian cancer cells, revealing its impact on glucose metabolism.

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

The paper introduces a modified decision tree model for proteomic data analysis, improving generalization across Alzheimer's disease datasets and identifying ferroptosis-related proteins as important in dementia resistance.

This study reanalyzes Orbitrap Astral DIA data using DirectMS1 to show it detects additional proteins and reveals new biological insights in disease-related samples.

This study shows that everolimus, a rapamycin analog, uniquely affects the ubiquitin-proteasome system by increasing ubiquitin levels and altering polyubiquitination patterns, distinct from its analogs.

This paper evaluates the efficiency of negative ion mode proteomics using an MS1-only approach and finds it can identify over 1,000 proteins in human cells with high accuracy.

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 validates amino acid variants in proteogenomics by using multiple reads from overlapping peptides to improve variant reliability.

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.

The paper identifies ADAR-mediated RNA editing sites in Drosophila proteomes across developmental stages and shows editing is phase-specific and enriched in synaptic and actomyosin functions.