Fig. 1

Flowchart of the MMHGAN model. The MMHGAN model consists of four stages. (i) Calculate the combined similarity between lncRNAs and diseases and collate the associations between lncRNAs and diseases and between miRNAs. (ii) Construct homogeneous graphs GL and GD based on the top k pieces of information with the highest similarity in the combined similarity matrix of lncRNAs and diseases derived from the KNN algorithm. Aggregated the neighbor node features through the multihead attention mechanism. (iii) Construct a heterogeneous graph G_lmd based on the association matrix, extract different types of metapaths from the graph, construct subgraphs, and update node embeddings through a graph attention network (GAT). Subsequently, calculated the weights under different metapaths and update the target node embeddings. (iv) Use the fully connected layer to recombine the input features to predict potential lncRNA-disease associations