| A neural network (NN) was trained on amino and nucleic acid sequences to test the NNs ability to predict a nucleic acid sequence given only an amino acid sequence. A multi-layer backpropagation network of one hidden layer with 5 to 9 neurons was used. Different network configurations were used with varying numbers of input neurons to represent amino acids, while a constant representation was used for the output layer representing nucleic acids. In the best-trained network, 93% of the overall bases, 85% of the degenerate bases, and 100% of the fixed bases were correctly predicted from randomly selected test sequences. The training set was composed of 60 human sequences in a window of 10 to 25 codons at the coding sequence start site. Different NN... |
