A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data.
Sign Up to like & getrecommendations! Published in 2023 at "Proteomics"
DOI: 10.1002/pmic.202200341
Abstract: Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. The… read more here.
Keywords: mass spectrometry; distance; crosslinking mass; range ... See more keywords
Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry
Sign Up to like & getrecommendations! Published in 2021 at "Nature Communications"
DOI: 10.1038/s41467-021-23441-0
Abstract: Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits… read more here.
Keywords: mass spectrometry; crosslinking mass; retention time; mass ... See more keywords
Breaking barriers in crosslinking mass spectrometry with enhanced throughput and sensitivity using Orbitrap Astral
Sign Up to like & getrecommendations! Published in 2025 at "Nature Communications"
DOI: 10.1038/s41467-025-64844-7
Abstract: Crosslinking mass spectrometry is an essential tool for probing protein-protein interactions and structural organization. We here compare Orbitrap Astral and Orbitrap Eclipse instruments using Cas9 crosslinked with PhoX and DSSO under standardized chromatographic and acquisition… read more here.
Keywords: orbitrap astral; spectrometry; mass spectrometry; crosslinking mass ... See more keywords