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A CLASSY method for the analysis of NMR spectral data
This Toolbox item describes an algorithm, database, or computational method for proteomics analyses.
1H-NMR spectra can contain a wealth of information, but the extraction and analysis of that information is still not trivial, especially for metabonomic studies of biofluids. Jeremy K. Nicholson and colleagues at Imperial College London have just developed a new method that may help, however. Called cluster analysis statistical spectroscopy (CLASSY), the untargeted, unsupervised approach groups local clusters of structurally related peaks. Then, a hierarchical clustering algorithm identifies global relationships among the clusters. In this way, researchers can assess the covariation of metabolites in biofluids in response to stimuli over time. The resulting data are presented as heat maps for easy visual interpretation.
To demonstrate the performance of CLASSY, Nicholson and colleagues applied it to the study of urine samples from rats with arginine-induced pancreatitis. The researchers say that the approach could be applied to various biological problems, such as the identification of small molecules that have novel activities and the study of host–pathogen interactions. (Anal. Chem. 2009, DOI 10.1021/ac901240j)
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