The Age of Data‐Driven Proteomics: How Machine Learning Enables Novel Workflows-Reference-Cited by-同舟云学术

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The Age of Data‐Driven Proteomics: How Machine Learning Enables Novel Workflows

Published:2020-06-25 Issue:21-22 Volume:20 Page:1900351
ISSN:1615-9853
Container-title:PROTEOMICS
language:en
Short-container-title:Proteomics

Author:

Bouwmeester Robbin¹²,Gabriels Ralf¹²^ORCID,Van Den Bossche Tim¹²,Martens Lennart¹²^ORCID,Degroeve Sven¹²

Affiliation:

1. VIB‐UGent Center for Medical Biotechnology VIB Albert Baertsoenkaai 3 B‐9000 Ghent Belgium

2. Department of Biomolecular Medicine Ghent University Albert Baertsoenkaai 3 B‐9000 Ghent Belgium

Funder

H2020 Research Infrastructures

Fonds Wetenschappelijk Onderzoek

H2020 Marie Skłodowska-Curie Actions

Publisher

Wiley

Subject

Molecular Biology,Biochemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/pmic.201900351

Reference79 articles.

1. Mass spectrometry-based proteomics

2. The diverse and expanding role of mass spectrometry in structural and molecular biology

3. Recognizing millions of consistently unidentified spectra across hundreds of shotgun proteomics datasets

4. A mass-tolerant database search identifies a large proportion of unassigned spectra in shotgun proteomics as modified peptides

5. Dynamic Spectrum Quality Assessment and Iterative Computational Analysis of Shotgun Proteomic Data

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