Nikolai Slavov

The paper introduces multiDIA, a proteomics method that improves sequence coverage and scalability in neurodegenerative disease studies by combining multiple proteases and data-independent acquisition.

The paper uses single-cell proteomics and transcriptomics to reveal cell-type-specific functional coordination in PBMCs, showing protein covariation that reflects protein-protein interactions and pathway rewiring.

The paper identifies abundant alternate translation products in human proteins, showing their association with protein stability and disease.

The paper shows proteomic asymmetry in mouse and human embryos that influences lineage segregation.

The paper quantifies protein synthesis and clearance across 4,200 cells, revealing that translation and clearance are linearly dependent on growth rate and identifying cell-type specific regulatory mechanisms.

The paper identifies NEPRO and C18ORF21 as constitutive subunits of metazoan RNase MRP, clarifying its composition and RNA binding specificity.

This study identifies proteomic changes in Alzheimer's disease, revealing decreased 20S proteasome levels and altered ubiquitin system enzymes contributing to protein accumulation.

JMod improves sequence identification and quantification in multiplexed DIA proteomics by jointly modeling overlapping mass spectra, enabling higher throughput with maintained accuracy.

timePlex increases LC-MS throughput by multiplexing samples in the time domain, achieving combinatorial scaling and enabling high-throughput proteomics.

PSMtags enhance peptide detection and sequence identification in proteomics, enabling 9-plexDIA and significantly increasing sample throughput.

The paper identifies a signature for protein leakage in single-cell proteomics and develops a classifier to detect damaged cells across species and cell types.

The paper quantifies how growth-dependent dilution and protein degradation affect protein abundance across human B-cells, tissues, and proteoforms, showing dilution explains 40% of abundance changes.

The paper shows that DDX3X and DDX3Y exhibit post-transcriptional cross- and auto-regulation, buffering their expression levels in human cells.

The paper quantifies proteomes and RNA levels in human testis cells to infer post-transcriptional regulation using a Bayesian model called BayesPG.

The paper identifies regulators of nucleocytoplasmic protein transport in macrophages using single-nucleus proteomics and validates findings through knockdown experiments.

The paper uses single-cell proteomics to show that advanced maternal age oocytes have reduced proteostasis and meiosis proteins.

The paper quantifies protein covariation in single human cells during EMT, revealing dynamic protein-protein correlations that reflect biological regulation masked by cluster-average dynamics.

DO-MS v2.0 optimizes DIA mass spectrometry parameters and quality control for single-cell proteomics, supporting label-free and plexDIA methods with interactive analysis and reporting.

This paper introduces plexDIA, a framework for increasing proteomics throughput and depth through multiplexed DIA, enabling more accurate protein quantification and single-cell analysis.

The paper introduces nPOP, a method for single-cell protein covariation analysis, revealing cell cycle dynamics and functional differences between melanoma subpopulations.

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.

This paper develops SCoPE2, a single-cell proteomic method, to analyze macrophage heterogeneity and finds a continuous proteome gradient in macrophages without polarizing cytokines.

This paper characterizes trade-offs in using isobaric carriers for proteomic analysis and provides strategies to optimize their use in different applications.

DART-ID improves single-cell proteome coverage by aligning retention times and using a Bayesian framework to enhance peptide identification and quantification.

DO-MS identifies and optimizes bottlenecks in LC-MS/MS methods by interactively visualizing and analyzing data from all analysis levels, improving ion delivery efficiency by 370% in one case.

SCoPE-MS combines acoustic cell lysis with isobaric tandem-mass-tag carrier channels to quantify over a thousand proteins in single mammalian cells, resolving cancer cell types and stem cell differentiation.

The paper develops a model to accurately quantify proteoform stoichiometries using mass-spectrometry data without external standards.

Minimal ProteOmic sample Preparation (mPOP) eliminates cleanup losses in single-cell mass spectrometry proteomics, enabling automated SCoPE-MS profiling that separates mammalian cells by cell type and cell-division-cycle phase.

The paper measures mRNA and protein levels during ESC differentiation, revealing widespread discordance and using a kinetic model to identify post-transcriptional regulation.

This study estimates the contribution of transcript levels to mean-level and across-tissues variability in protein abundance, finding that post-transcriptional regulation significantly influences across-tissues variability.