Skip to main content


Figure 3 | BMC Bioinformatics

Figure 3

From: Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

Figure 3

Decision tree for the evaluation of individual mutations. A decision tree (A) was constructed in order to evaluate the contribution of a mutation to amyloidogenicity. A path is followed for each mutation, depending on its position and exposure, as well as on the increase or decrease in sheet-forming propensity associated with it. Each path leads to one of eight terminal nodes, which is associated with a score, defined as the product of the weights (in italics) along the path leading to it. An analysis of paths taken by amyloidogenic and non-amyloidogenic derivatives of the different germlines indicated that different pairs of terminal nodes may be used to provide maximum separation between these derivatives. For instance, amyloidogenic derivatives of X93627 mostly end in leaf 1, while the non-amyloidogenic counterparts are more frequently associated with leaf 7; germline derivatives that can be distinguished using specific terminal nodes are indicated in the illustration. Based on this analysis, a final tree (B) was created which branches first on the basis of the germline to which the derivative being tested belongs; the structure and weights of the original tree (A) are kept. Each edge emanating from a germline node is connected to a copy of the original tree, where weights on paths which could be used for maximizing the separation between amyloidogenic and non-amyloidogenic derivatives are either boosted or decreased tenfold. For the illustrative example in (B), paths for J00248 (Germline 1) and Z22208 (Germline n) are shown.

Back to article page