Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich
science. Protein sequences and structures are comprehensively catalogued in online …

In recent years machine learning has made extensive progress in modeling many aspects of
mass spectrometry data. We brought together proteomics data generators, repository …

The inclusion of peptide retention time prediction promises to remove peptide identification
ambiguity in complex liquid chromatography–mass spectrometry identification workflows …

Mass-spectrometry-based proteomics enables quantitative analysis of thousands of human
proteins. However, experimental and computational challenges restrict progress in the field …

Interest in the use of machine learning for peptide fragmentation spectrum prediction has
been strongly on the rise over the past years, especially for applications in challenging …

Mass spectrometry is the driving force behind current brain proteome analysis. In a typical
proteomics approach, a protein isolate is digested into tryptic peptides and then analyzed by …

In the last decade, a revolution in liquid chromatography-mass spectrometry (LC-MS) based
proteomics was unfolded with the introduction of dozens of novel instruments that …

Rising population density and global mobility are among the reasons why pathogens such
as SARS-CoV-2, the virus that causes COVID-19, spread so rapidly across the globe. The …

A lot of energy in the field of proteomics is dedicated to the application of challenging
experimental workflows, which include metaproteomics, proteogenomics, data independent …

Spectrum library searching is a powerful alternative to database searching for data
dependent acquisition experiments, but has been historically limited to identifying previously …