Kuhn S - Search Results

1

Data Fusion-based Discovery (DAFdiscovery) pipeline to aid compound annotation and bioactive compound discovery across diverse spectral data.

Borges RM, das Neves Costa F, Chagas FO, Teixeira AM, Yoon J, Weiss MB, Crnkovic CM, Pilon AC, Garrido BC, Betancur LA, Forero AM, Castellanos L, Ramos FA, Pupo MT, Kuhn S. Borges RM, et al. Among authors: kuhn s. Phytochem Anal. 2023 Jan;34(1):48-55. doi: 10.1002/pca.3178. Epub 2022 Oct 3. Phytochem Anal. 2023. PMID: 36191930

2

Applying NMR compound identification using NMRfilter to match predicted to experimental data.

Kuhn S, Colreavy-Donnelly S, de Andrade Silva Quaresma LE, de Andrade Silva Quaresma E, Borges RM. Kuhn S, et al. Metabolomics. 2020 Nov 21;16(12):123. doi: 10.1007/s11306-020-01748-1. Metabolomics. 2020. PMID: 33222074

3

Combining high-speed countercurrent chromatography three-phase solvent system with electrospray ionization-mass spectrometry and nuclear magnetic resonance to profile the unconventional food plant Syzygium malaccense.

Lopes AG, Borges RM, Kuhn S, Garrett R, Costa FDN. Lopes AG, et al. Among authors: kuhn s. J Chromatogr A. 2022 Aug 16;1677:463211. doi: 10.1016/j.chroma.2022.463211. Epub 2022 Jun 23. J Chromatogr A. 2022. PMID: 35810640

4

An integrated approach for mixture analysis using MS and NMR techniques.

Kuhn S, Colreavy-Donnelly S, Santana de Souza J, Borges RM. Kuhn S, et al. Faraday Discuss. 2019 Aug 15;218(0):339-353. doi: 10.1039/c8fd00227d. Faraday Discuss. 2019. PMID: 31114813

5

A pilot study for fragment identification using 2D NMR and deep learning.

Kuhn S, Tumer E, Colreavy-Donnelly S, Moreira Borges R. Kuhn S, et al. Magn Reson Chem. 2022 Nov;60(11):1052-1060. doi: 10.1002/mrc.5212. Epub 2021 Sep 21. Magn Reson Chem. 2022. PMID: 34480494

6

Computational simulation of ¹ H NMR profiles of complex biofluid analyte mixtures at differential operating frequencies: Applications to low-field benchtop spectra.

Edgar M, Kuhn S, Page G, Grootveld M. Edgar M, et al. Among authors: kuhn s. Magn Reson Chem. 2022 Dec;60(12):1097-1112. doi: 10.1002/mrc.5236. Epub 2022 Jan 17. Magn Reson Chem. 2022. PMID: 34847251

7

A data-oriented approach to making new molecules as a student experiment: artificial intelligence-enabling FAIR publication of NMR data for organic esters.

Rzepa HS, Kuhn S. Rzepa HS, et al. Among authors: kuhn s. Magn Reson Chem. 2022 Jan;60(1):93-103. doi: 10.1002/mrc.5186. Epub 2021 Jun 16. Magn Reson Chem. 2022. PMID: 34106480

8

NMReDATA: Tools and applications.

Kuhn S, Wieske LHE, Trevorrow P, Schober D, Schlörer NE, Nuzillard JM, Kessler P, Junker J, Herráez A, Farès C, Erdélyi M, Jeannerat D. Kuhn S, et al. Magn Reson Chem. 2021 Aug;59(8):792-803. doi: 10.1002/mrc.5146. Epub 2021 Apr 8. Magn Reson Chem. 2021. PMID: 33729627

9

Applications of machine learning and artificial intelligence in NMR.

Kuhn S. Kuhn S. Magn Reson Chem. 2022 Nov;60(11):1019-1020. doi: 10.1002/mrc.5310. Magn Reson Chem. 2022. PMID: 36225085 No abstract available.

10

The Three Pillars of Natural Product Dereplication. Alkaloids from the Bulbs of Urceolina peruviana (C. Presl) J.F. Macbr. as a Preliminary Test Case.

Lianza M, Leroy R, Machado Rodrigues C, Borie N, Sayagh C, Remy S, Kuhn S, Renault JH, Nuzillard JM. Lianza M, et al. Among authors: kuhn s. Molecules. 2021 Jan 26;26(3):637. doi: 10.3390/molecules26030637. Molecules. 2021. PMID: 33530604 Free PMC article.

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