Chemoproteomics aims to achieve precise and comprehensive quantification of protein–small molecule interactions, yet methodological comparisons across quantitative proteomics workflows remain scarce.....

We’ve documented more than 100 instances of apparent data manipulation in Thermo’s catalog

🚀 We’re hiring in Omics Science and Technology at Cellzome / GSK (Heidelberg)! Excited to share that we have two open roles in Proteomics & Metabolomics. We’re looking for talented scientists who want...

Accurate spectral libraries are essential for analyzing data-independent acquisition (DIA) proteomics data. Here, the authors present Carafe, which trains on DIA data to build experiment-specific spec...

Comparison of DIA to spectral counting and TMT quantitative techniques using animal lens studies - pwilmart/quantitative_proteomics_comparison

A theoretical foundation for entrapment methods is presented, along with a method that enables more accurate evaluation of false discovery rate (FDR) control in proteomics mass spectrometry analysis p...

Despite great progress, sample preparation remains an area for improvement in proteomics, particularly for low-input samples where conventional protocols lead to losses and incomplete digestion. We pr...

Liquid chromatography-mass spectrometry (LC-MS) can enable precise and accurate quantification of analytes at high-sensitivity, but the rate at which samples can be analyzed remains limiting. Throughp...

Proteomic experiments, particularly those addressing dynamic proteome properties, time series, or genetic diversity, require the analysis of large sample numbers. Despite significant advancements in p...

Data-independent acquisition mass spectrometry (DIA-MS) has emerged as a key technology in quantitative proteomics. Here, the authors introduce DIA-BERT, a transformer model pre-trained on existing DI...

Quantitative readout is essential in proteomics, yet current bioinformatics methods lack a framework to handle the inherent multi-level nature of the data (fragments, MS1 isotopes, charge states, modi...

We introduce here a novel approach, termed time-segmented acquisition (Seg), to enhance the identification of peptides and proteins in trapped ion mobility spectrometry (TIMS)-time-of-flight (TOF) mas...

We are excited to announce DIA-NN 2.0, the most significant milestone in the history of DIA-NN development. Key Breakthroughs Proteoform Confidence mode: DIA-NN 2.0 solves the long-standing chall...

Data-independent acquisition (DIA) on ion mobility mass spectrometers enables deep proteome coverage and high data completeness in large-scale proteomics studies. For advanced acquisition schemes such as parallel accumulation serial fragmentation-based DIA (diaPASEF) stability of ion mobility (1/K0) over time is crucial for consistent data quality. We found that minor changes in environmental air pressure systematically affect the vacuum pressure in the TIMS analyzer, causing ion mobility shifts. By comparing experimental ion mobilities with historical weather data, we attributed observed drifts to fluctuations in the ground air pressure. Moderate air pressure changes of e.g. fifteen mbar induce ion mobility shifts of 0.025 Vs/cm2. These drifts negatively impact peptide quantification across consecutively acquired samples due to drift-dependent abundance changes and increased missing values for ions located at the boundaries of diaPASEF isolation windows, which cannot be corrected by postprocessing. To address this, we applied an in-batch mobility autocalibration feature on a run-wise basis, leading to full elimination of ion mobility drifts.