Authors


Dr. Piotr Klukowski

Department of Chemistry and Applied Biosciences, ETH Zürich

Vladimir-​Prelog-Weg 2
8093 Zürich
Switzerland

E-mail: piotr.klukowski@phys.chem.ethz.ch

Prof. Dr. Peter Güntert

Department of Chemistry and Applied Biosciences, ETH Zürich
Faculty Biochemisty, Chemistry, and Pharmacy, Goethe-University Frankfurt am Main
Department of Chemistry, Tokyo Metropolitan University

Vladimir-​Prelog-Weg 2
8093 Zürich
Switzerland

E-mail: peter.guentert@phys.chem.ethz.ch

Prof. Dr. Roland Riek

Department of Chemistry and Applied Biosciences, ETH Zürich

Vladimir-​Prelog-Weg 2
8093 Zürich
Switzerland

E-mail: roland.riek@phys.chem.ethz.ch


Publications

To support our work, cite the following articles:
  • Klukowski, P., Riek, R. & Güntert, P. Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA (2022). Nature Communications 13, 6151. (https://doi.org/10.1038/s41467-022-33879-5)
  • Klukowski, P., Augoff, M., Zięba, M., Drwal, M., Gonczarek, A., & Walczak, M. J. (2018). NMRNet: a deep learning approach to automated peak picking of protein NMR spectra. Bioinformatics, 34, 2590-2597.
  • Schmidt, E., & Güntert, P. (2012). A new algorithm for reliable and general NMR resonance assignment. Journal of the American Chemical Society, 134, 12817-12829.
  • Güntert, P. & Buchner, L. (2015). Combined automated NOE assignment and structure calculation with CYANA. J. Biomol. NMR 62, 453-471.
  • Güntert, P., Mumenthaler, C. & Wüthrich, K. (1997). Torsion angle dynamics for NMR structure calculation with the new program DYANA. J. Mol. Biol. 273, 283-298.

Acknowledgements

  • ARTINA has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie grant agreement No. 891690


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