Vadim Demichev

The paper shows that alpha-synuclein phase separation can form Lewy body-like structures without pre-existing seeds, suggesting a new mechanism for neurodegeneration.

SILAC-Site directly measures phosphosite stoichiometries without enrichment, showing low stoichiometry for most phosphopeptides and correlating with direct detection.

Pho-Tip is a one-pot dephosphorylation method that improves the detection of low-abundant phosphorylated peptides in DIA phosphoproteomics data.

pmultiqc generates metadata-aware QC reports for proteomics data using standardized metrics and integrates with existing workflows and cloud services.

The paper evaluates ZT Scan DIA, a proteomics method combining scanning DIA with ion trapping, showing improved precursor and protein identification, quantification, and bias reduction in multi-species mixtures.

The paper benchmarks proteomics accuracy using a large-scale dataset, identifying systematic errors and providing a resource for method optimization and software evaluation.

The paper compares DIA and DDA methods for immunopeptidomics, showing DIA improves detection of low-abundant bacterial epitopes from Listeria monocytogenes.

This paper introduces a one-pot LC/MS-based method to quantitatively map protease substrate specificity using a large peptide library.

Proteomics and ubiquitinomics screening of 100 CRBN ligands in two cell lines validated 50 novel neosubstrates and yielded selective phenyl glutarimide degraders of KDM4B, G3BP2 and VCL.

The paper quantifies proteomic effects of aneuploidy in natural yeast isolates, finding chromosome-wide dosage compensation in the proteome but not transcriptome.

CysQuant quantifies cysteine oxidation and protein abundance using DDA or DIA-MS, revealing redox changes in Arabidopsis exposed to light.

This study identifies Cystatin C as a glucocorticoid-responsive factor that recruits Trem2+ macrophages and predicts immunotherapy failure in cancer.

QuantUMS, a machine-learning module in DIA-NN, weights MS1 and fragment signals by quality-derived variance estimates, improving DIA precision, removing ratio compression in high-accuracy mode, and scoring each quantity's reliability.

The paper records proteomes for non-essential gene knock-outs in yeast to uncover principles of protein expression and annotate gene function.

The paper shows yeast cells can cooperatively compensate for methionine auxotrophy by using a new homocysteine synthase, HSU1, to re-assimilate hydrogen sulfide.

The paper introduces MSFragger-DIA, a tool for fast and sensitive peptide identification from DIA proteomics data, integrated into FragPipe, and demonstrates its performance across various sample types.

MSBooster improves peptide identification rates by integrating deep learning-based features into existing workflows with MSFragger and Percolator.

Multiplexing nonisobaric isotopologous mass tags (mTRAQ) with data-independent acquisition and DIA-NN increases sensitive proteomics throughput 3-fold while cutting missing data below 3% in bulk and single cells.

The paper demonstrates improved proteomic depth using DIA-NN and FragPipe for dia-PASEF data, achieving higher sensitivity and quantification in complex samples.

OxoScan-MS enables sensitive and scalable glycoproteome profiling of plasma samples, revealing differential glycosylation in severe COVID-19 patients.

This paper introduces Scanning SWATH, a proteomics method that enables high-throughput quantification by using fast chromatographic gradients and improves precursor identification.

Neural-network ensembles scoring 69 peak features, plus fragment interference subtraction, boost data-independent acquisition (DIA) proteomics identifications and quantification precision, especially with short chromatographic gradients.