Advanced Proteomics Techniques and Applications

The paper introduces Percolator-RESET, a post-processor for tandem mass spectrometry proteomics that better controls the false discovery rate than Percolator.

InstaNovo is a transformer model for de novo peptide sequencing that outperforms existing methods, enabling accurate identification of peptides and discovery of novel sequences and organisms.

The paper identifies challenges in validating isobaric histone peptidoforms using mass spectrometry and proposes strategies to improve their identification.

This paper introduces a novel MS score framework for analyzing polyclonal antibodies, demonstrating its ability to identify antibody subgroups and predict interactions.

The paper introduces OnePotNTA, a one-pot method for quantifying N-terminal acetylation in mycobacteria, achieving high coverage and reducing sample preparation time.

This paper introduces a time-lapse proteomic method to improve ECM protein sequence coverage and identify differential trypsin susceptibility.

The paper uses laser microdissection and proteomics to compare tumor and stroma in HNSCC tissues, identifying ECM enrichment in stroma and potential targets for disease intervention.

MetaboMiNR is a web tool for analyzing label-free proteomic data, focusing on metabolism and nuclear receptors, with features for pathway analysis, gene extraction, and plot generation.

The paper profiles proteome and phosphoproteome dynamics during neuronal differentiation of the KOLF2.1J iPSC line, revealing distinct molecular signatures and kinase activity changes.

omicsGMF integrates dimensionality reduction, batch correction, and imputation for bulk and single-cell proteomics data, improving statistical power for differential abundance detection.

The paper uses quantitative cross-linking and mass spectrometry data to cluster cross-links by their conformational state preferences, providing insights into protein conformational plasticity across different biological contexts.

This study modifies K-CLIP to identify PKA substrates, discovering SMC3 as a novel substrate and demonstrating the method's versatility for kinase-substrate profiling.

This paper introduces a machine learning-assisted Full Window DIA method for top-down proteomics, enhancing signal intensity and sequence coverage in protein analysis.

This study identifies virus protein fragments in urine proteomics of febrile patients, revealing potential viral causes of fever and demonstrating high reliability in detection.

DiNovo improves de novo peptide sequencing by using mirror proteases and deep learning, achieving higher coverage and confidence than single-protease methods.

The paper constructs a co-regulation map of phosphosites using machine learning and phosphoproteomic data, revealing kinase-substrate associations and identifying potential therapeutic targets in cancer.

This paper develops a rapid proteomics method using HTA protease and LC-MS to quantify blood biomarkers in under an hour.

This paper introduces a visible-light-controlled cross-linking method for analyzing protein complexes and dynamic interactions in live cells, showing improved accuracy and temporal control.

This paper introduces a method to improve protein turnover rate calculation using heavy water labeling and mass spectrometry, increasing coverage of well-fitted peptides by 25-82% in mouse organ proteomes.

This paper introduces a novel framework for harmonizing pan-cancer proteomics data, demonstrating its effectiveness in improving dataset integration and revealing prognostic markers.

The paper investigates how endemic viral infections alter the neuronal proteome and links these changes to neurodegenerative disease pathways.

This study presents a proteomic and phosphoproteomic analysis of the human cell cycle in non-transformed cells, revealing new insights into cell cycle-dependent protein and phosphorylation oscillations.

The paper provides an updated Candida albicans PeptideAtlas proteomics resource with detailed PTM data and tools for analysis.

The paper improves bacterial epitope discovery by integrating multiple search engines and rescoring, increasing peptide identification by 27% and detecting 18 new bacterial peptides.

The paper develops a method to discover RNA-protein-small molecule complexes using proteome-wide stability assays and applies it to identify novel DDX helicase targets of rocaglates.

ClassiCOL improves species classification from ancient collagen LC-MS/MS data by resolving peptide ambiguity through isoBLAST and taxonomic branching analysis.

The paper develops a targeted LC-MS method to quantify SARS-CoV-2 spike protein expression and enables proteome profiling of infected cells.

AlphaQuant improves proteoform regulation detection in bottom-up proteomics by using tree-based quantification and deep learning, revealing new patterns in mouse tissues.

This paper develops a spatial proteomics workflow to identify and map proteoforms in human kidney tissue, revealing spatially distinct proteomic profiles between glomeruli and tubules.

This paper introduces a 96-sample western blot format that improves efficiency and capacity while maintaining compatibility with standard protocols.