A general hypergraph learning algorithm for drug multi-task predictions in micro-to-macro biomedical networks
Fig 2
The sub-figure (a) depicts all the motifs presented in our work. DRSS(Ij), DISS(Ip), DRSM (Ii), DISM(Iu) denote the four motif-driven hypergraphs constructed on drug related and have the same substructure, drug independent and have the same substructure, drug related and have the same molecular interactions, and drug independent and have the same molecular interactions motifs groups, respectively. The sub-figure (b) is a real example of driving the hypergraph base on triangular motif. It shows that the hypergraph method will make the relation between some nodes with high-order relations closer. The sub-figure (c) draws the process of multi-branches hypergraph attention and graph convolutional networks inferring new drug-related interactions.