An ensemble of artificial neural networks has been trained on a set of experimentally
solved protein structures to predict the relative exposure of the amino acids. The method assigns
a reliability score to each surface accessibility prediction as an inherent part of the training process.
This is in contrast to the most commonly used procedures where reliabilities are obtained by postprocessing
the output.