Modeling the adaptive immune system: predictions and simulations

Lundegaard, Claus; Lund, Ole; Kesmir, Can; Brunak, Søren; Nielsen, Morten

Several prediction methods have been made publicly available, and when selecting between these several cautions should be taken. The published performance, and how it is evaluated should be examined, but it is also very important that the method is able to generate predictions for the actual allele of interest. A major study comparing the predictive performance of a large part of the available methods was recently performed by Peters et al. (2006) showing that in general the SMM and the ANN methods (Table 1 ) perform the best, even when taken into account the number of training data for each method. The cross-validated performance of these methods for several human and mouse MHC class I alleles was compared with the best performing other method available as web tool. The full results of this work are listed in Supplementary Table 1 . The tools and URLs are listed in Table 1 . It should be mentioned, however, that tools known to be trained on a significant part of the test set were excluded from this comparison. To achieve binding predictions for an allele with uncharacterized specificity, the supertype concept (Sette and Sidney, 1998) can be used for the limited number of alleles with well-defined supertype relationships (Lund et al., 2005) . Note, however, that predictions with methods predicting the specific allele is most often to be preferred, as the accuracy of these will be better (Nielsen et al., 2007a) .