Advanced Proteomics Techniques and Applications

A Pubic Hair Is 172 Times More Pubic Than a Scalp Hair

This study uses proteomics to distinguish scalp hair from pubic hair, identifying specific keratin-associated proteins and amino acid compositions as markers for anatomical origin.

Foundation Model Enables Interpretable Open and Error-Tolerant Searching for Mass Spectrometry-Based Proteomics

The paper introduces yHydra, a foundation model for mass spectrometry-based proteomics that enables open and error-tolerant peptide and protein identification with improved performance.

PAC/SP3 on-bead carboxyl derivatization allows combined C- and N-terminomics

This paper introduces an on-bead PAC/SP3 derivatization method for C- and N-terminomics, demonstrating its application in identifying C-terminal peptides and analyzing termini in Jurkat cells.

Learning Fragmentation Physics or Exploiting Sequence Priors? Benchmarking Bias in Deep Learning Models for De Novo Peptide Sequencing

This paper benchmarks prior bias in deep learning models for de novo peptide sequencing using a novel framework called DeNovo-PBI.

False discovery rate control enables trustworthy deep-learning-based de novo peptide sequencing

This paper introduces a method to control false discovery rates in deep-learning-based de novo peptide sequencing, improving reliability of peptide identifications.

AutoPELSA: an automated sample preparation system for proteome-wide identification of target proteins of diverse ligands

AutoPELSA automates the PELSA workflow for proteome-wide ligand-protein interaction detection, enabling high-throughput analysis of both strong and low-affinity ligands.

MassSpectrum Analyzer: An interactive platform for proteomic searching parameter refinement and peptide modification focused re-scoring

The paper introduces MassSpectrum Analyzer, a tool for refining proteomic search parameters and re-scoring peptides with modifications, improving detection of highly modified peptides and quantifying fragmentation patterns.

ProteoMeter: A pipeline for integrating multi-PTM and limited proteolysis data to reveal modification-structure coupling at the residue level

ProteoMeter integrates multi-PTM and limited proteolysis data to map proteomic changes to residue level, demonstrating its use in analyzing HCoV-229E infection.

Systematic optimization and benchmarking of synchro-PASEF for high-throughput phosphoproteome profiling

This paper optimizes and benchmarks synchro-PASEF for phosphoproteomics, showing improved identification and quantification with retention time summation, and comparable performance to dia-PASEF in modeling phosphosignaling.

Community Resource: A Genome-Based Extension of Large-Scale Wheat Proteogenomics

The paper develops a genome-based proteogenomics workflow for wheat, reanalyzing proteomics data to refine gene models and provide a community resource for genome annotation.

gamdid: generalized additive models for differential distributions in single cell experiments

gamdid is a statistical framework for differential distribution analysis in single-cell proteomics, detecting shape differences and outperforming existing methods for such cases.

Quantitative interactome mapping of skeletal muscle insulin resistance

This study quantifies global PPI changes in skeletal muscle insulin resistance using PCP-MS and qXL-MS, revealing dysregulated interactions with chaperones and PDIA6.

DiaReport: Reproducible Workflow for Differential Expression Analysis and Interactive Reporting in DIA-based Proteomics

DiaReport provides a reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics, demonstrating its utility with an extracellular vesicle dataset.

DLDN-Bench: A Benchmark Framework for Deep Learning De Novo Peptide Sequencing in Proteomics

DLDN-Bench benchmarks deep learning de novo peptide sequencing tools using human mass spectrometry data, showing performance improvements over traditional methods.

A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High Performance Proteomics Analysis

This paper introduces PAMAF, a novel DIA-MS mode using HRIM for proteomics, achieving higher sensitivity and efficiency in protein identification and quantification.

Low-input proteomics enables proteome and phosphoproteome-scale molecular phenotyping of separase-deficient oocytes

The paper uses low-input proteomics to compare proteome and phosphoproteome changes in wild-type and separase-deficient mouse oocytes, revealing specific alterations in chromosome-associated proteins.

πDIA-CLIP: efficient identification of highly heterogeneous proteomics data via a generalized zero-shot framework

The paper introduces πDIA-CLIP, a zero-shot framework for DIA proteomics data analysis that improves protein identification and reduces false positives across diverse datasets.

Rapid Histone Post-Translational Modification Analysis Using Alternative Proteases and Tandem Mass Tags

This paper introduces RIPUP, a rapid protease-based workflow for histone PTM analysis, showing improved PTM coverage and quantitative accuracy using TMT labeling and complementary proteases.

A DIA-based quantitative crosslinking mass spectrometry framework for dynamic structural proteomics

This paper introduces DIA-QCLMS, a framework for quantitative crosslinking mass spectrometry that improves confidence assessment and integrates structural features, showing improved reproducibility in analyzing protein dynamics.

Sample preparation for mass spectrometry-based tissue (phospho)proteomics

The paper describes a protocol for preparing tissue samples for proteome and phosphoproteome analysis using mass spectrometry, including steps for tissue disruption, lipid depletion, and phosphopeptide enrichment.

Spatial distribution of the proteome in human body and cancers

The paper presents a comprehensive spatial proteome map of human tissues and cancers, enabling drug response analysis and target discovery.

The Single Cell Proteomic blueprint, navigating instrumentation platforms, software tools and high-load libraries in neutrophils, RKO and A549 cells

This study evaluates DIA search engines, high-load libraries, and instrumentation platforms for single-cell proteomics across different cell types.

Detection of Melanoma Using Deep Serum Proteome Profiling and Machine Learning

This study detects melanoma using serum proteome profiling and machine learning, identifying eight protein biomarkers with high diagnostic accuracy.

AliceDB database and pipeline for identification of natural protein variants based on mass spectrometry measurement data

AliceDB is a database of over 7 million natural protein variants for Homo sapiens, improving proteomic data interpretation by accounting for natural variation.

PeptiDIA: A Machine Learning Framework for Enhanced Peptide Identification in Fast-Gradient Data-Independent Acquisition Proteomics

PeptiDIA enhances peptide identification in fast-gradient DIA data using machine learning, improving identification depth by 25-34% in human and murine datasets.

Development of a Xylene-Free Sample Preparation Protocol for Quantitative Proteomics of Clinically Relevant Formaldehyde-Fixed Paraffin-Embedded Needle Biopsy Samples

This study develops a xylene-free proteomics protocol for FFPE needle biopsy samples, showing distinct proteomic patterns in liver conditions.

Optimised haemoglobin depletion improves clinical proteomics from dried blood spots

This paper optimizes haemoglobin depletion in dried blood spots to improve proteomic analysis, increasing protein identifications by ~50% and enabling biomarker discovery in CKD patients.

SPOTTER: Automated Tissue-Barcoding Platform for Spatial Proteomics and Phosphoproteomics

SPOTTER enables automated, high-plex spatial proteomics and phosphoproteomics by barcoding proteins on tissue sections, achieving deep coverage with LC-MS/MS.

Label-free quantification in the Crux toolkit

The paper introduces a label-free quantification feature in the Crux toolkit, demonstrating improved efficiency and accuracy compared to existing methods.

Comparative Evaluation of DDA and DIA Based Proteomic Workflows in Beryllium Related Lung Disease

This study compares DDA-MS and DIA-MS for proteomic analysis of lung compartments in beryllium-related disease, finding DIA-MS provides better quantitative completeness and detects more low-abundance proteins.