Cross-peak classification in two-dimensional nuclear magnetic resonance spectra using a two-layer neural network
✍ Scribed by Simon A. Corne; Julie Fisher; A. Peter Johnson; William R. Newell
- Publisher
- Elsevier Science
- Year
- 1993
- Tongue
- English
- Weight
- 781 KB
- Volume
- 278
- Category
- Article
- ISSN
- 0003-2670
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✦ Synopsis
Ahstraet A two-layer simulated neural network has been trained to classify cross-peaks in two-dimensional nuclear magnetic resonance spectra. Examples of peaks for both network training and testing were selected by an experienced spectroscopist. The trained network has been used to classify previously unseen data. Spectral artefacts and authentic cross-peaks are distinguished. Peaks whose shapes have been modified, for example by overlap, are classified correctly. A spectrum for phoratoxin B, a protein of 46 amino acid residues, is used to illustrate the training and performance of the network.