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Mini-conference: Machine Learning in NMR and Structural Biology

Research

The Swedish NMR Centre organizes a mini-conference on the utility of machine learning in contemporary NMR and structural biology.

Conference
Date
27 Sep 2023
Time
09:40 - 15:20

Topics

•    AlphaFold for protein structure and dynamics
•    Conformational ensembles of the human IDP proteome
•    NUS spectra by neural networks
•    Non-stationary NMR
•    NMR spectral analysis by machine-learning techniques
•    Advanced database searching

Venue & Address: Swedish NMR Centre, University of Gothenburg,  Medicinaregatan 16A, 41390 Gothenburg and over Zoom:

https://gu-se.zoom.us/j/63448914100?pwd=MmI5WTl3MkdRbTF1TGo4eDhScm5CQT09 Passcode: 991893


Organizers: Vladislav Orekhov, Göran Karlsson; Chemistry & Molecular Biology & Swedish NMR Centre, University of Gothenburg, Sweden; Ilya Kuprov, University of Southampton, UK


Registration and Contact: via e-mail to bionmr.snc@gmail.com

Program Mini-conference 27th of Sept 2023

09.40 – 10.00 Coffee

Session I, Chair: Göran Karlsson (University of Gothenburg, Sweden)


10.00 – 10.30 Title TBA. Simon Bruderer, (Bruker Biospin, Switzerland)

10.30 – 11.00 The functional dynamics of K-Ras and its G12C and G12D oncogenic mutants. Rafael Bruschweiler, (Ohio State University, USA)

11.00 – 11.30 Predicting alternate conformational states with AlphaFold2 and sequence clustering. Hannah K Wayment-Steele (Brandeis University, USA)

11.30 – 12.00 Magnetstein. Quantitative NMR mixture analysis robust to low-resolution, disturbed lineshapes, and peak shifts. Krzysztof Kazimierczuk (University of Warsaw, Poland)

12.00 – 13.20 Lunch

Session II, Chair: Krzysztof Kazimierczuk (University of Warsaw, Poland)


13.20 – 13.50 Title TBA. Ilya Kuprov, (University of Southampton, UK)

13.50 – 14.20 Beyond traditional NMR signal processing with Deep Learning. Vladislav Orekhov, (University of Gothenburg, Sweden)

14.20– 14.50 Conformational ensembles of the intrinsically disordered proteome. Giulio Tesei, (Copenhagen University, Danmark)

14.50– 15.20 Using deep learning to unleash the full potential of NMR spectroscopy. D. Flemming Hansen, (UCL, London, UK)