  The neural network techniques are developed for artificial sequences based on
approximate models of proteins. We only encode the hydrophobicity of the amino
acid side chains without attempting to model the secondary structure. We use
our approach to obtain a large set of sequences with known 3-D structures for
training the neural network. By employing recurrent neural networks we describe
a way to augment a neural network to deal with sequences of realistic length
and long-distant interactions between the sequence regions.
