Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution-Reference-Cited by-同舟云学术

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Predicting the number of sulfur atoms in peptides and small proteins based on the observed aggregated isotope distribution

Published:2021-08-05 Issue:19 Volume:35 Page:
ISSN:0951-4198
Container-title:Rapid Communications in Mass Spectrometry
language:en
Short-container-title:Rapid Commun Mass Spectrom

Author:

Claesen Jürgen¹²³^ORCID,Valkenborg Dirk³,Burzykowski Tomasz³⁴

Affiliation:

1. Department of Epidemiology and Data Science, Amsterdam UMC VU University Amsterdam Amsterdam The Netherlands

2. Microbiology Unit SCK‐CEN Mol Belgium

3. I‐Biostat, Data Science Institute Hasselt University Hasselt Belgium

4. Department of Statistics and Medical Informatics Medical University of Bialystok Bialystok Poland

Publisher

Wiley

Subject

Organic Chemistry,Spectroscopy,Analytical Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rcm.9162

Reference19 articles.

1. The isotopic distribution conundrum

2. The Analysis of Peptide-Centric Mass-Spectrometry Data Utilizing Information About the Expected Isotope Distribution

3. Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

4. De novo prediction of the elemental composition of peptides and proteins based on a single mass

5. IUPAC Periodic Table of the Elements and Isotopes (IPTEI) for the Education Community (IUPAC Technical Report)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning approach for the prediction of the number of sulphur atoms in peptides using the theoretical aggregated isotope distribution;Rapid Communications in Mass Spectrometry;2023-03-08

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