Proteomics

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ProteomeTools – Part II - Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning

ABSTRACT: "The ProteomeTools project aims to derive molecular and digital tools from the human proteome to facilitate biomedical and life science research. Here, we describe the second iteration of the generation and multimodal LC-MS/MS analysis of >220,000 synthetic tryptic peptides representing nearly all canonical human gene products. This resource will be extended to 1.4 million peptides and all data will be made available to the public in ProteomicsDB."

INSTRUMENT(S): Orbitrap Fusion ETD

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Daniel Zolg  

LAB HEAD: Bernhard Kuster

PROVIDER: PXD010595 | Pride | 2019-05-21

REPOSITORIES: Pride

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Publications

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  ...[more]

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