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Visualization of metabolomics data

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Workshop Metabolomics Athens November 2012  http://www.metabolomicsworkshop2012.com 16

Visualization of metabolomics data

    Matthias Scholz  IASMA Research and Innovation Centre Fondazione Edmund Mach, Trendo Italy    In my talk, I will give an overview about modern machine learning techniques for analysing the  huge number of features in metabolite data. I will introduce Independent Component Analysis  (ICA) as a useful alternative to classical Principal Component Analysis. I will show in which cases  a  Support  Vector  Machine  (SVM)  can  be  appropriate  for  biomarker  detection.  And  I  will  talk  about time course analysis and how to analysis and visualize the nonlinear data structure. This  will be completed by showing some examples in Matlab. 

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