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Informatics Colloquium 10.12. 2019, 14:00 lecture hall D2 doc. RNDr. Tomáš Brázdil, Ph.D., FI MU Pushing the limits in automated NMR structure determination Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is a technique for determining the structural and dynamic properties of molecules. NMR relies on properties of certain atomic nuclei that, when placed in a strong magnetic field, resonate at characteristic frequencies. NMR spectroscopy generates complex data whose analysis is a laborious task and the road to NMR structure is generally a long one. The chief barrier is that existing methodologies require a significant amount of spectrometer time (several weeks), and effort by a trained expert (up to several months). So fully automatic methods for NMR structure determination are in demand. In my talk, I will concentrate on the problem of assigning given resonant frequencies (chemical shifts) from NMR spectra to the nuclei of a protein. Our attempts at solving this demanding problem comprise both machine learning as well as elementary graph theoretic methods. I will start with the machine learning problem of predicting an amino acid type based on a given set of chemical shifts. Consequently, I will show how such a prediction can be incorporated into an algorithm for complete assignment of chemical shifts to atoms in a protein using, among other methods, simple graph algorithms. I will also present open problems and deficiencies of our current method which is still under development.