Figure 2

Estimating the significance of pathway rankings provided by pathway selection. For phenotypes that are weakly associated with the presence or absence of specific metabolic pathways, the classification quality should be within the same range for classification based on randomly picked pathways (red), all pathways (marked by a horizontal line), and pathways highly ranked in attribute subset selection (green, ReliefF; yellow, SVMAttributeEval; blue, wrapper (naïve Bayes)). As an example, the right diagram shows the classification quality for the phenotype 'habitat: soil' (depending on the number of top-ranking pathways used for classification). In this case, the top-ranking pathways provided by attribute subset selection are considered as not significant for the phenotype. The left diagram shows the classification quality values for the phenotype 'obligate intracellular'. Using the most relevant pathways for classification results in higher classification quality compared to using all pathways or randomly picked pathways. Furthermore, the quality values lie above 0.6. In this case, the most relevant pathways derived by attribute subset selection are considered as significant.