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The NMRPredict Desktop module, offered as part of Mnova and supplied to us by Modgraph, relies to a large extent for its accuracy on the databases behind it. In the case of carbon-13 prediction the database already contains nearly half a million assigned spectra under ongoing validation and curation. However, the accuracy of prediction depends not just on the size of the database but on its relevance to you and your chemistry.

Professor Robien and his team of co-workers in Vienna are able to abstract about 15,000 assigned NMR data each year from the literature. Which journals (and years of publication) have been extracted from during the past decade can be seen here.

Now which data is abstracted can be driven by you! All we need to know is which journals contain the most relevant assigned NMR data for your work.

Simply send Professor Robien an email at: telling him which journals are of most value to you in terms of relevant ASSIGNED NMR data. Please note that the word assigned is critical. Journals which include NMR data consisting of chemical structures and NMR peak lists, but with no assignment of the peaks to the atoms in the molecule, are of no use to a prediction program. We can only abstract assigned data.

We will reply to you after collecting your responses. If we are already abstracting from the journals you suggest we will tell you so and refer you to: for more details. If we are not abstracting from the journals you suggest we will tell you if and when we will start abstracting from those journals.

Once we have abstracted from the journals and added the data to our collection we will let you know as soon as they are available.

Therefore all we ask from you is a list of the journals you read which include the most relevant assigned NMR data for your field of chemistry. Hopefully within a very short time we will be able to include that data in our collections, which will immediately improve the predictions you receive from NMRPredict Desktop!

If you have any questions please send them to Jeff Seymour at

Last modified: May 23, 2014 by Olalla Lema