Rows of Position Specific Scoring Matrices selected for neural network input: Network inputs consist of the PSSM of the target residue and its two neighboring residues on C- and N-terminals. Each residue is thereby represented by a 20 dimensional vector with integer values. These values represent (logarithmic) effective frequencies of occurrence at respective positions in a multiple alignment. Neural network input layer is therefore made of 20 × 5 = 100 units. Two units in the only hidden layer and one unit in the output layer add up to a total of 202 neural units to be trained in the fully connected neural network.