Generating high quality libraries for DIA MS with empirically corrected peptide predictions
Data-independent acquisition-mass spectrometry (MS) typically requires many preparatory MS runs to produce experiment-specific spectral libraries. Here, the authors show that empirical correction of in silico predicted spectral libraries enables efficient generation of high-quality experiment-specif...
Main Authors: | Brian C. Searle, Kristian E. Swearingen, Christopher A. Barnes, Tobias Schmidt, Siegfried Gessulat, Bernhard Küster, Mathias Wilhelm |
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Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2020-03-01
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Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-020-15346-1 |
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