Publications

• Main manuscript that describes ARTINA method for automated chemical shift assignment and structure determination:
  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)
• NMRtist online platform that hosts ARTINA with computational resources available to non-commercial users:
  Klukowski, P., Riek, R. & Güntert, P. NMRtist: an online platform for automated biomolecular NMR spectra analysis, Bioinformatics, 2023. (https://doi.org/10.1093/bioinformatics/btad066)
• Structure based assignment and ARTINA integration with AlphaFold:
  Klukowski, P., Riek, R. & Güntert, P. Time-optimized protein NMR assignment with an integrative deep learning approach using AlphaFold and chemical shift prediction, Science Advances, 2023. (https://www.science.org/doi/full/10.1126/sciadv.adi9323)

• 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