Many research questions in fields such as personalized medicine, drug screens or systems
biology depend on obtaining consistent and quantitatively accurate proteomics data from …

The recent development of machine learning methods to identify peptides in complex mass
spectrometric data constitutes a major breakthrough in proteomics. Longstanding methods …

This review provides a brief overview of the development of data‐independent acquisition
(DIA) mass spectrometry‐based proteomics and selected DIA data analysis tools. Various …

Data-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic
methodology that generates permanent digital proteome maps offering highly reproducible …

Inflammasome is an intracellular signaling complex of the innate immune system. Activation
of inflammasomes promotes the secretion of interleukin 1β (IL-1β) and IL-18 and triggers …

The data‐independent acquisition mass spectrometry (DIA‐MS) has rapidly evolved as a
powerful alternative for highly reproducible proteome profiling with a unique strength of …

Data-independent acquisition (DIA) is an emerging technology for quantitative proteomic
analysis of large cohorts of samples. However, sample-specific spectral libraries built by …

There remains a significant gap in our quantitative understanding of crosstalk between
apoptosis and necroptosis pathways. By employing the SWATH-MS technique, we …

Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is the main
method for high-throughput identification and quantification of peptides and inferred …

Data-independent acquisition (DIA) is an emerging mass spectrometry (MS)-based
technique for unbiased and reproducible measurement of protein mixtures. DIA tandem …