Based on z'(v), an outlier detection algorithm for the identification of the strategic molecules is performed. The feature values in the network are best described by a power law distribution. This means, that most nodes have very similar feature values, but the ones that are different differ a lot. They are exceptional in their feature value. With regard to the considered features, we find that sample strategic molecules rank very high. However, we do not suggest using the absolute values for finding feature specific thresholds for the classification; these will depend on the network size and centre, and introduce more human bias. Instead, we classify them based on the feature distribution.