This following is a pdf of a tutorial presented at Metabolomics 2006 in Boston on 26 June 2006:

Multivariate statistical analyses and machine learning for metabolomics

Free Chemometrics Software can be downloaded from the PyChem website.

Below are some useful references on data analysis and in particular evolutionary computational algoithms:

Jarvis, R.M. & Goodacre, R. (2005) Genetic algorithm optimisation for pre-processing and variable selection of spectroscopic data. Bioinformatics 21, 860-868.
Goodacre, R. (2005) Making sense of the metabolome using evolutionary computation: seeing the wood with the trees.  Journal of Experimental Botany 56, 245-254.
Goodacre, R. Vaidyanathan, S., Dunn, W.B., Harrigan, G.G. & Kell, D.B. (2004) Metabolomics by numbers – acquiring and understanding global metabolite data.  Trends in Biotechnology 22, 245-252.
Goodacre, R. (2003) Explanatory analysis of spectroscopic data using machine learning of simple, interpretable rules.  Vibrational Spectroscopy 32, 33-45.
Beavis, R.C., Colby, S.M., Goodacre, R. Harrington, P.B., Reilly, J.P., Sokolow, S. & Wilkerson, C.W. (2000) Artificial intelligence and expert systems in mass spectrometry.  In Encyclopedia of Analytical Chemistry. Ed. Meyers, R.A., pp. 11558–11597.