Articles | Volume 4, issue 1
https://doi.org/10.5194/mr-4-19-2023
https://doi.org/10.5194/mr-4-19-2023
Research article
 | 
08 Feb 2023
Research article |  | 08 Feb 2023

DEEP Picker1D and Voigt Fitter1D: a versatile tool set for the automated quantitative spectral deconvolution of complex 1D-NMR spectra

Da-Wei Li, Lei Bruschweiler-Li, Alexandar L. Hansen, and Rafael Brüschweiler

Viewed

Total article views: 2,182 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,567 559 56 2,182 50 46
  • HTML: 1,567
  • PDF: 559
  • XML: 56
  • Total: 2,182
  • BibTeX: 50
  • EndNote: 46
Views and downloads (calculated since 15 Nov 2022)
Cumulative views and downloads (calculated since 15 Nov 2022)

Viewed (geographical distribution)

Total article views: 2,182 (including HTML, PDF, and XML) Thereof 2,079 with geography defined and 103 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
Short summary
Recent advances in machine learning have opened new opportunities toward the automated analysis and spectral reconstruction of highly complex NMR spectra, including ones encountered in metabolomics. We demonstrate the combined power of the deep neural network DEEP Picker 1D and the Voigt Fitter1D software for the quantitative streamlined analysis of 1D 1H NMR spectra, extending the reach of a wide range of NMR applications.