Pavel G. Sinitcyn

Disentangling maternal pregnancy and fetal-specific plasma signatures through integrated proteomics and site-specific N-glycoproteomics

The paper identifies pregnancy-specific and fetal-specific plasma proteomic and N-glycoproteomic signatures by comparing maternal, cord blood, and non-pregnant control samples.

Protein Language Model Decoys for Target Decoy Competition in Proteomics: Quality Assessment and Benchmarks

This paper introduces a protein language model-based decoy generation method for proteomics and benchmarks it against classical decoy strategies, finding it less distinguishable by neural networks but not superior in search performance.

Rapid Peptide Mapping of Monoclonal Antibodies with Direct Infusion Mass Spectrometry

This paper introduces RaPiD-mAb-MS, a direct infusion mass spectrometry method for rapid peptide mapping of monoclonal antibodies, achieving 100-fold faster analysis with high sequence coverage and comparable results to conventional methods.

Systematic benchmarking of mass spectrometry-based antibody sequencing reveals methodological biases

This study benchmarks mass spectrometry-based antibody sequencing methods, revealing biases related to sequence, concentration, protease, and bioinformatics tools.

A Technical Evaluation of Plasma Proteomics Technologies

This paper evaluates six plasma proteomic technologies, finding that Seer Proteograph XT provides the highest proteomic depth and quantification, while Olink Explore HT shows comparable LOD but worse LOQ.

Deep Learning Predicts Non-Normal Peptide FAIMS Mobility Distributions Directly from Sequence

The paper develops deep learning models to predict FAIMS ion mobility of peptides from sequence, achieving high F2 score on E. coli peptides.

Fast and Deep Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer

The paper introduces a method using the Orbitrap Astral mass spectrometer with DIA to rapidly analyze phosphoproteomes, detecting over 80,000 phosphorylation sites in mice.