Advanced Proteomics Techniques and Applications

IsoAnalytics: A Single-cell Proteomics Web Server

IsoAnalytics provides a user-friendly web server for analyzing and visualizing single-cell proteomics data from the Isoplexis platform, accessible to non-experts.

Insight on physicochemical properties governing peptide MS1 response in HPLC-ESI-MS/MS proteomics: A deep learning approach

The paper develops a deep learning model to predict peptide MS1 intensities using sequence data and identifies key physicochemical properties influencing the response.

High Field Asymmetric Waveform Ion Mobility Spectrometry- Mass Spectrometry to Enhance Cardiac Muscle Proteome Coverage

This study adapts high-field asymmetric ion mobility spectrometry (FAIMS) coupled with mass spectrometry to improve cardiac muscle proteome coverage with reduced sample handling and processing time compared to traditional methods.

Finding Haplotypic Signatures in Proteins

The paper investigates how common genetic haplotypes affect proteomic search results and identifies multi-variant peptides detectable by mass spectrometry.

An integrated view of baseline protein expression in human tissues

The paper reanalyzes 24 public proteomics datasets to assess baseline protein abundance in 31 human organs and integrates the results into the Expression Atlas for combined proteomics and transcriptomics analysis.

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis

This study introduces a streamlined TMT labeling method using pre-aliquoted dry reagents, improving efficiency and reducing variability in proteomic and metaproteomic analyses.

Exploring functional protein covariation across single cells using nPOP

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

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

MD 2.0 is a web-based platform for quantitative proteomics data analysis that enables modular, customizable workflows to accelerate insight generation and collaboration.

MSstatsPTM: Statistical relative quantification of post-translational modifications in bottom-up mass spectrometry-based proteomics

The paper introduces a statistical framework for detecting differential post-translational modification abundance in proteomics data, showing improved fold change estimation and detection compared to existing methods.

Exhaustive Cross-linking Search with Protein Feedback

This paper introduces ECL-PF, a method for cleavable XL-MS data analysis that improves sensitivity in detecting protein-protein interactions and structures.

Characterization of protein isoform diversity in human umbilical vein endothelial cells (HUVECs) via long-read proteogenomics

The paper uses long-read proteogenomics to characterize protein isoform diversity in HUVECs, identifying novel transcripts and isoforms with potential functional implications.

A de novo MS1 feature detector for the Bruker timsTOF Pro

This paper introduces a de novo feature detector, 3DID, for analyzing timsTOF Pro data, which identifies more peptide features across a broader abundance range than existing tools.

Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography

The paper develops a tailored DIA method for single-cell proteomics to improve quantification from low-input samples and establishes a complete scp-MS workflow.

AlphaPeptDeep: A modular deep learning framework to predict peptide properties for proteomics

AlphaPeptDeep predicts peptide properties using deep learning, offering a modular framework that matches or exceeds existing tools for retention time, ion mobility, and fragment intensity prediction.

Monitoring regional astrocyte diversity by cell-type specific proteomic labeling in vivo

The paper establishes a mouse line for cell-type specific proteomic labeling and identifies regional astrocyte proteome differences using mass spectrometry.

Deep Proteome Profiling Reveals Signatures of Age and Sex Differences in Paw Skin and Sciatic Nerve of Naïve Mice

This study uses deep proteome profiling to identify age and sex differences in mouse paw skin and sciatic nerve, revealing significant protein and network variations with implications for disease models.

Current state, existing challenges, and promising progress for de novo sequencing and assembly of monoclonal antibodies

This study evaluates de novo sequencing tools for monoclonal antibodies, finding that deep learning methods improve recall but challenges remain in heavy chain sequencing.

SEPepQuant enables comprehensive protein isoform characterization in shotgun proteomics

SEPepQuant improves protein isoform characterization in shotgun proteomics by addressing limitations in existing methods, identifying isoform-level regulation events, and enabling cross-study comparisons.

Generalized peakgroup scoring boosts identification rates and accuracy in mass spectrometry based discovery proteomics

This paper introduces GPS, a machine learning-based method for improving peptide and protein identification accuracy and rates in DIA proteomics by using an external dataset, and demonstrates its effectiveness in identifying biomarkers for acute kidney injury.

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data

The paper introduces pyAscore, a Python package for scoring PTM localization in mass spectrometry data, enhancing workflow integration and versatility.

Coisolation of peptide pairs for peptide identification and MS/MS-based quantification

The paper introduces a method to coisolate and fragment SILAC peptide pairs for improved identification and quantification in MS/MS-based proteomics.

One-stop analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform

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.

Ion mobility-resolved phosphoproteomics with dia-PASEF and short gradients

This study demonstrates the application of dia-PASEF with TIMS to achieve high-throughput phosphoproteomics with short gradients, quantifying over 12,000 phosphopeptides in one hour.

High sensitivity limited material proteomics empowered by data-independent acquisition on linear ion traps

The paper develops a method combining linear ion traps and FAIMS for low-input proteomics, improving sensitivity and throughput for limited material samples.

Characterization of peptide-protein relationships in protein ambiguity groups via bipartite graphs

This study analyzes bipartite peptide-protein graphs in proteomics, showing how graph structures vary with data type and organism, and highlights the challenge of quantifying proteins without unique peptides.

MSBooster: Improving Peptide Identification Rates using Deep Learning-Based Features

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

Open modification searching of SARS-CoV-2-human protein interaction data reveals novel viral modification sites

The paper reanalyzes public mass spectrometry data to identify post-translational modifications in SARS-CoV-2-host protein interactions, revealing novel modification sites and their potential functional roles.

Newfound coding potential of transcripts unveils missing members of human protein communities

The paper identifies 280 alternative proteins in human protein-protein interaction networks using proteogenomic data and experimental validation, revealing new interactions and functional roles.

Improving peptide-level mass spectrometry analysis via double competition

The paper improves peptide-level mass spectrometry analysis by showing that double competition (PSM-and-peptide) outperforms single competition (PSM-only) in discovering peptides at a 1% FDR threshold.

Cell type-independent profiling of interactions between intracellular pathogens and the human phosphoproteome

The paper develops a platform to profile interactions between intracellular pathogens and the human phosphoproteome, identifying host-pathogen interactomes and expanding knowledge of viral protein function.