Fig. 1

Data flow diagram that shows our supervised link prediction algorithm to predict in vivo drug sensitivity. (a) The training and test data are provided to the supervised link prediction algorithm. (b) A feature vector construction method is applied to the training and test data, to obtain new feature representations of the training and test data. (c) A link filtering algorithm is applied to the new feature representation of the training data, to yield subsampled data. (d) A learning algorithm takes as input the subsampled data, to induce the model h. (e) The model h is applied to the new feature representation of the test data, to yield predictions