FNTM can be used to predict functionally-related genes in a particular tissue context. The inputs to the prediction are (i) a set of genes to be used as positive labels in an SVM classifier and (ii) name of the tissue for which the predictions are made. The output of the prediction consists of an expanded set of genes and the corresponding prediction scores, which is the distance of each gene from the fitted hyperplane.