Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1181053 | Chemometrics and Intelligent Laboratory Systems | 2013 | 6 Pages |
•We used trees to represent NMR spectra allowing for fast similarity search.•Our method is very compact and is suitable for high dimensional spectra.•The number of nodes grows almost linearly with the number of peaks.•We tested our approach for proton, carbon and HSQC spectra.
An efficient method to extract and store information from NMR spectra is proposed that is suitable for comparison and construction of a search engine. This method based on trees doesn't require any peak picking or any pre-treatment of the data and is found to outperform the currently available methods, both in terms of compactness and velocity. Our approach was tested for 1D proton spectra and 2D HSQC spectra and compared with the method proposed by Pretsch and coworkers [1] and [2] [Bodis et al. 2007, Bodis et al. 2009]. Additionally, the correspondence between spectral and structural similarity was evaluated for both methods.