Toward Diagnosis of Diabetes by NMR and Mulitvariate Analysis: Study of 1H NMR Spectra of Human Serum in an Integrated Working Environment
Poster Nov 01, 2006
Chen Peng, Omoshile Clement, Gregory Banik, Scott Ramos, Tao Wang, and Bin Xia
Data analysis is one of the key steps involved in any metabolomics studies, and processing of NMR data is especially tedious and timeconsuming since it involves multiple steps to transform and correct the data starting from the raw FIDs. In order to improve the efficiency of NMR-based metabolomics studies, we have developed KnowItAll® Informatics System, Metabolomics Edition as a consistent and integrated software environment that covers the entire process from processing raw NMR data —to multivariate analysis—to biomarker identification. Using two datasets of 1H NMR spectra of mouse urine and human serum, we demonstrate the high efficiency of this integrated workflow for metabolomics data analysis.
We developed an automated sample preparation protocol based on a robotic platform PAL RTC (CTC Analytics AG, Zwingen Switzerland), which represent a modified Bligh and Dyer method producing samples for both hydrophilic metabolomics using GC-MS and lipidomics using SFC-MS simultaneously.READ MORE