Advanced Proteomics Techniques and Applications

The paper optimizes automated phosphopeptide enrichment to improve phosphoproteome coverage and sensitivity in low-input samples using LC-MS/MS.

The paper introduces an automated sample preparation workflow for laser microdissection guided proteomics, validated on human tonsil tissue with high cell type specificity.

One-Tip provides a proteomics method for high-depth protein identification from minimal cell samples and single zygotes with high throughput.

The paper evaluates the detection of amino acid substitutions in shotgun proteomics by creating a ground-truth library using mixed bacterial proteomes and identifies sources of bias in substitution identification.

AlphaPept is an open-source framework for efficient processing of large MS-based proteomics datasets, achieving significant speed improvements using Python and machine learning.

The paper analyzes mass spectrometry data to identify alternative splicing-derived protein variants in human heart chambers, finding tissue-specific isoforms and their functional implications in protein binding.

The paper develops a low-input proteomics method called LASP to improve peptide recovery and reduce MS contamination, achieving 1,175 proteins identified per single cell.

The paper introduces a rapid, high-throughput proteomics sample processing protocol called Heat n Beat, achieving consistent peptide yield and quality across diverse tissue types in under an hour.

Crema is an open-source Python tool that implements target-decoy competition methods for estimating false discovery rates in proteomics experiments.

CURTAIN and CURTAIN-PTM are web-based tools for exploring and sharing MS-based proteomics data, enabling non-experts to analyze and visualize results through interactive features and shareable links.

This study develops a method to analyze the human lung ECM proteome using photocleavable surfactant and diaPASEF, identifying nearly 400 unique matrisome proteins.

This study uses mass spectrometry proteomics to identify protein altering variants and map pQTLs, confirming target specificity and identifying novel variants not accessible by affinity proteomics.

The paper introduces ContamSPOT, a method to detect and remove trace contaminants in mass spectrometry samples using TLC plates, improving data quality and instrument longevity.

This study uses proteome-wide thermal shift assays to analyze over a million thermal stability measurements from 96 compounds in cells and 70 in lysates, revealing target engagement and off-target effects.

The paper introduces InSeqAPI and PairQuant to enhance ABPP throughput and reproducibility using hyperplexing and IDA, identifying new druggable sites in nuclear proteins.

The paper introduces a benchmarking procedure and software for evaluating LC-MS/MS performance in bottom-up proteomics, enabling comparison of workflows and error detection.

This study uses FAIMS to identify novel legumain substrates in murine spleen by improving neo-N-termini detection in proteomic analyses.

This study explores the use of charge state distribution (CSD) in proteomics to enhance peptide identification and distinguish intramolecular interactions in phosphopeptides.

The paper analyzes proteomics data to identify cancer-testis antigens (CTAs) in healthy and tumor tissues, finding 22 significantly enriched, 42 tumor-exclusive, and 32 healthy-abundant CTAs.

The paper introduces HaloMS, a high-throughput method for mapping protein interactions in adipocytes, identifying new transcription factor complexes and networks.

NovoLign provides a de novo metaproteomics pipeline for rapid taxonomic profiling and reference database creation, offering an alternative to database-based spectral annotation.

RokaiXplorer provides an intuitive web tool for phospho-proteomic data analysis and visualization, offering multiple functionalities and interactive features for researchers without specialized training.

The paper develops a workflow to enrich newly synthesized proteins in microbial communities using BONCAT and click chemistry, demonstrating its application in tracing microbial activity.

PepPre improves peptide identification by detecting accurate and comprehensive precursor ions, leading to higher PSM and peptide identifications compared to existing methods.

DeepRescore2 improves phosphopeptide identification using deep learning, leading to more phosphosites detected and new biological insights in liver cancer.

This paper introduces PgxSAVy, a tool for quality control of variant peptides in proteogenomics, which improves accuracy in identifying true variants and annotates their disease relevance.

The paper introduces msqrob2PTM, a workflow for differential abundance and usage analysis of PTMs and peptidoforms in proteomics data, showing it performs on par or better than existing methods.

iSanXoT provides a standalone tool for integrative analysis of quantitative proteomics data, offering features like error distribution modeling and workflow customization.

This study improves RNA-interactome detection using DIA SILAC over DDA SILAC, achieving higher protein detection and lower variation with single-shot analysis.

The paper develops a causal model to assess and correct ratio compression caused by ion interference in multiplex proteomics data.