A computer-implemented method of training a neural network-implemented model for predicting the pathogenicity of variants, wherein the neural network processes sequences of amino acids and accompanying position frequency matrices (PFMs), wherein PFMs indicate the frequency of every amino acid at each amino acid position, the method including: generating, based upon missense training example sequence pairs each comprising a reference amino acid sequence and an alternative amino acid sequence that includes a variant such that the alternative amino acid sequence is different to the reference amino acid sequence of the missense training example sequence pair, supplemental benign training example sequence pairs, that include a start location, through a target amino acid location, to an end location, wherein each supplemental benign training example sequence pair: comprises a reference amino acid sequence and an alternative amino acid sequence; has a reference amino acid sequence and an alternative amino acid sequence that matches the start location and the end location of reference and alternative amino acid sequences of a corresponding missense training example sequence pair; and has a reference amino acid sequence and an alternative amino acid sequence that are identical; inputting with each supplemental benign training example sequence pair a supplemental training PFM that is identical to a PFM of the corresponding missense training example at the matching start and end location; and training the neural network-implemented model using the supplemental benign training example sequence pairs, the supplemental training example PFMs, the corresponding missense training example sequence pairs, and the PFMs of the missense training example sequence pairs at the matching start and end locations; whereby training influence of the training PFMs is attenuated during the training; and whereby the neural network, after training, is configured to predict whether an amino acid sequence is pathogenic or not pathogenic. generating, based upon missense training example sequence pairs each comprising a reference amino acid sequence and an alternative amino acid sequence that includes a variant such that the alternative amino acid sequence is different to the reference amino acid sequence of the missense training example sequence pair, supplemental benign training example sequence pairs, that include a start location, through a target amino acid location, to an end location, wherein each supplemental benign training example sequence pair: comprises a reference amino acid sequence and an alternative amino acid sequence; has a reference amino acid sequence and an alternative amino acid sequence that matches the start location and the end location of reference and alternative amino acid sequences of a corresponding missense training example sequence pair; and has a reference amino acid sequence and an alternative amino acid sequence that are identical; comprises a reference amino acid sequence and an alternative amino acid sequence; has a reference amino acid sequence and an alternative amino acid sequence that matches the start location and the end location of reference and alternative amino acid sequences of a corresponding missense training example sequence pair; and has a reference amino acid sequence and an alternative amino acid sequence that are identical; inputting with each supplemental benign training example sequence pair a supplemental training PFM that is identical to a PFM of the corresponding missense training example at the matching start and end location; and training the neural network-implemented model using the supplemental benign training example sequence pairs, the supplemental training example PFMs, the corresponding missense training example sequence pairs, and the PFMs of the missense training example sequence pairs at the matching start and end locations; whereby training influence of the training PFMs is attenuated during the training; and whereby the neural network, after training, is configured to predict whether an amino acid sequence is pathogenic or not pathogenic.