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Document type:
Zeitschriftenaufsatz 
Author(s):
Gessulat, Siegfried; Schmidt, Tobias; Zolg, Daniel Paul; Samaras, Patroklos; Schnatbaum, Karsten; Zerweck, Johannes; Knaute, Tobias; Rechenberger, Julia; Delanghe, Bernard; Huhmer, Andreas; Reimer, Ulf; Ehrlich, Hans-Christian; Aiche, Stephan; Kuster, Bernhard; Wilhelm, Mathias 
Title:
Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning 
Abstract:
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impairs the realization of the full potential of these approaches. Here, we extended the ProteomeTools synthetic peptide library to 550,000 tryptic peptides and 21 million high-quality tandem mass spectra. We trained a deep neural network, termed Prosit, r...    »
 
Journal title:
Nature Methods 
Year:
2019 
Journal volume:
16 
Journal issue:
Pages contribution:
509-518 
Publisher:
Springer Science and Business Media LLC 
E-ISSN:
1548-70911548-7105 
Date of publication:
27.05.2019