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orthogonal-signal-correction
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Advantage of applying OSC to 1H NMR-based metabonomic data of celiac disease
, Article International Journal of Endocrinology and Metabolism ; Volume 10, Issue 3 , 2012 , Pages 548-552 ; 1726913X (ISSN) ; Fathi, F ; Darvizeh, F ; Zali, M. R ; Nejad, M. R ; Rostami, K ; Tafazzoli, M ; oskouie, A. A ; Mortazavi Tabatabaei, S. A ; Sharif University of Technology
2012
Abstract
Background: Celiac disease (CD) is a disorder associated with body reaction to gluten. After the gluten intake, an immune reaction against the protein occurs and damages villi of small intestine in celiac patients gradually. Objectives: The OSC, a filtering method for minimization of inter- and intra-spectrom-eter variations that influence on data acquisition, was applied to biofluid NMR data of CD patients. Patients and Methods: In this study, metabolites of total 56 serum samples from 12 CD patients, 15 CD patients taking gluten-free diet (GFD), and 29 healthy cases were analyzed using nuclear magnetic resonance (NMR) and associated theoretical analysis. Employ-ing ProMetab (version...
Discrimination of wines based on 2D NMR spectra using learning vector quantization neural networks and partial least squares discriminant analysis
, Article Analytica Chimica Acta ; Volume 558, Issue 1-2 , 2006 , Pages 144-149 ; 00032670 (ISSN) ; Bouveresse, D. J. R ; Vercauteren, J ; Jalali Heravi, M ; Rutledge, D. N ; Sharif University of Technology
2006
Abstract
The learning vector quantization (LVQ) neural network is a useful tool for pattern recognition. Based on the network weights obtained from the training set, prediction can be made for the unknown objects. In this paper, discrimination of wines based on 2D NMR spectra is performed using LVQ neural networks with orthogonal signal correction (OSC). OSC has been proposed as a data preprocessing method that removes from X information not correlated to Y. Moreover, the partial least squares discriminant analysis (PLS-DA) method has also been used to treat the same data set. It has been found that the OSC-LVQ neural networks method gives slightly better prediction results than OSC-PLS-DA © 2005...