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Cluster 4

Fig. 4.14 Dendrogram based on PyMS data showing percentage similarity between 22 brewing strains of S. cerevisiae (redrawn from Timmins et al., 1998) Ale (A) and lager (L) strains are identified by their 'BB' coding.

Cluster 4

Fig. 4.14 Dendrogram based on PyMS data showing percentage similarity between 22 brewing strains of S. cerevisiae (redrawn from Timmins et al., 1998) Ale (A) and lager (L) strains are identified by their 'BB' coding.

A relatively new and exciting development in PyMS is the application of 'artificial neural networks' (AAN) to uncover complex relationships in multivariate data. Goodacre and Kell (1996) have described the use and benefits of'supervised learning' through AANs over the 'unsupervised learning' of PCA and CVA. The chief advantages for PyMS of such 'trained' AANs are in routine discrimination of closely related biological samples, quantification and screening of microbial cultures and

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