Sequence motif logo. A list of 100,000 random naturally occurring peptides with length L = motif length+2 * flank length, generated from random UniProt [46] sequences, is presented to the individual networks in the ensemble. For each network, the 1% peptides that obtain the highest prediction scores are used to create a position specific scoring matrix (PSSM) that represents the motif captures by the neural network. Using a Gibbs sampler approach, all PSSMs are aligned to maximize the information content of the combined matrix. This ''offset correction'' step is obtained by repeatedly attempting to shift the starting position of randomly chosen PSSMs, and accepting/rejecting the move according to the conventional Metropolis Monte Carlo probability relation [47] :