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.
Automating Mass Spectrometry-Based Quantitative Glycomics using Tandem Mass Tag (TMT) Reagents with SimGlycanPoster
One of the emerging trends in glycomics research is the innovation related to accurate MS based quantitative analysis of glycans.READ MORE
RAMclust/RAMsearch: efficient post-XCMS feature clustering and annotation of MS-based metabolomics datasetsPoster
Chromatographically coupled mass spectrometry is a powerful tool for profiling, semi-quantitatively or quantitatively, a breadth of small molecules with sensitivity and selectivity.READ MORE
Highly Accurate HCV Genotyping by Targeted Next Generation SequencingPoster
The recent fast advancement of next generation sequencing (NGS) technologies allowing for unprecedented speed and accuracy in analyzing viral genomes are opening new ways to further improve diagnostic genotyping of HCV.
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Tackling the Challenges of Artificial Intelligence
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