Where DI is the change in information content between the new and old offset configuration and T is a scalar that is lowered during the calculation. The process assigns to each PSSM, and to its relative network, an offset value that quantifies the shift distance from other networks. The re-aligned cores from the 1% scoring of 100,000 peptides are finally used to generate a combined sequence logo with the WebLogo program [48] . The offset correction can be skipped if the user chooses to, and in this case the logo is simply created by presenting the list of random peptides to the ANN final ensemble and selecting the 1% peptides that obtain the overall best score. Evaluation data. Additional data not included in the training can be uploaded to the NNAlign Server as an evaluation set. Evaluation data must be a list of peptides, with or without associated values, or a file in FASTA format. In the first case, all peptides are run through the trained network ensemble, and scored accordingly to their best alignment core. If values are provided together with peptides, they are assumed to be target values for validation purposes, and statistical measures between these values and predictions are calculated. In the case a FASTA file is loaded as evaluation set, the sequences therein contained are cut into peptides of length L = motif length+2 * flank length, shifting the starting position of one amino acid at a time. The generated peptides are all fed to the network to identify those that most closely match the motif learned by the ANNs. The results are sorted by prediction value, so that the best candidates are displayed at the top of the list.