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For these reasons it is impossible to construct any NMR-data evaluation wizard, like the automatic assignment module, without an extensive usage of statistical methods, allowing for a degree of logical “fuzziness”.
In our case this is done by applying at every step, to the full depth of the algorithm, a proprietary scoring system approach.
P NMR methodology was validated using standard solutions of model compounds and has excellent accuracy and repeatability.
NMR spectroscopy was proved to be a powerful tool for the determination of these bioactive molecules and will be an important aid for scientists who will perform interaction studies with these compounds, as well as researchers who need to determine and quantify them at their native sources.The Auto Assignment Algorithm combines several software techniques we had developed in recent years as tools for expert tasks such as automatic detection and characterization of spectral peaks, automatic solvent detection, and automatic structure verification (for which the auto-assignment feature is, in its own term, a building block).Real-life spectra always contain a number of artifacts such as noise, baseline distortions, relaxation and radiation-damping induced distortions of peak intensities, lineshape distortions due to magnetic field inhomogeneity, lineshape distortions due to unresolved weak long-range couplings, second-order interactions, peaks crowding causing peaks and multiplets to overlap, etc.Unfortunately, such a tool is only available in CSI (although it’s not uncommon that scientific progress was first visualized in fiction!), so for now we will have to settle for applications that can be used to assign known molecules to their corresponding 1H NMR.Using another sophisticated fuzzy-logic algorithm, each peak in the GSD list is classified according to whether it belongs to the compound, solvent, an impurity, an artifact, a 13C satellite, etc (Fig.3).The algorithm even attempts to pinpoint possible labile peaks.And this is, in our opinion, already a very valuable tool, especially today, when the volume of acquire data has increased inversely to the amount of analytical human resources and (sometimes) training.As a response to this necessity, we have developed an expert system for the automatic assignment of H NMR spectra of small molecules.Whilst a variety of computational methods to automatically assign NMR spectra of biomolecules have been in use since the early 90s, approaches for the unattended assignment of 1H NMR spectra of small spectra have been more sparse.Of course, having the ability to fully automatically elucidate an unknown structure from just a 1H NMR spectrum would be the ultimate goal of any computer based expert system.