by Scott Anthony Robson Ph. D. | March 8, 2019, 7:58 p.m.
In this series of articles, we will explore how Nuclear Magnetic Resonance (NMR) data is stored and processed. To do this, we will use the Python (Python 3) programming language to manipulate data from Bruker (and eventually Varian/Agilent) spectrometers. Python is an easy to read programming language which will allow us to not only describe the operations involved in data processing but actually work with real data and see the results.
Unlike some other biophysical techniques, the data from the NMR spectrometer:
can have high dimensionality, these higher dimensions need to be acquired in 'quadrature' (more on that later)
has dimensions that are often truncated (time constraints cuts down amount of data we can collect)
has strong signals from molecules we don't care so much about - like a concentration of 110 M 1H atoms present in the water required to dissolve some of our molecules.
All these problems need to be mitigated to some extent. We will visit these problems and how we mitigate them as we move from raw NMR data to spectra we can interpret.
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