Fig. 2 | Nature Communications

Fig. 2

From: A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

Fig. 2

Schematic illustration of compact feature learning. The random walk with restart (RWR) algorithm is first used to compute the diffusion states of individual networks. Then the low-dimensional representations of feature vectors for individual nodes are obtained by minimizing the difference between the diffusion states s i and the parameterized multinomial logistic models \({\hat s_i}\). The learned low-dimensional feature vectors encode the relational properties (e.g., similarity), association information and topological context of each node in the heterogeneous network. More details can be found in the main text

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