We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural
networks and new quantification and signal correction strategies for the processing of data-…

The COVID-19 pandemic is an unprecedented global challenge, and point-of-care
diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput …

Microbial communities are composed of cells of varying metabolic capacity, and regularly
include auxotrophs that lack essential metabolic pathways. Through analysis of auxotrophs for …

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection
to severe organ damage and death. We characterized the time-dependent progression of …

A challenge in solving the genotype-to-phenotype relationship is to predict a cell's
metabolome, believed to correlate poorly with gene expression. Using comparative quantitative …

The dia-PASEF technology uses ion mobility separation to reduce signal interferences and
increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-…

Mass spectrometry (MS)-based ubiquitinomics provides system-level understanding of
ubiquitin signaling. Here we present a scalable workflow for deep and precise in vivo …

Current mass spectrometry methods enable high-throughput proteomics of large sample
amounts, but proteomics of low sample amounts remains limited in depth and throughput. To …

Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become
technically feasible. While such analysis has the potential to accurately quantify thousands …

Liquid chromatography (LC) coupled with data-independent acquisition (DIA) mass spectrometry
(MS) has been increasingly used in quantitative proteomics studies. Here, we present …