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Fig. 1 | BMC Medical Informatics and Decision Making

Fig. 1

From: EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network

Fig. 1

Flow chart of EOESGC. Step 1 is to construct the coupled heterogeneous graph. FS is the functional similarity of miRNA, MFS is the Gaussian kernel similarity of miRNA, DSS is the semantic similarity of disease, DGS is the Gaussian kernel similarity of disease, and A is miRNA-disease association matrix. Step 2 is to use the EOE model to learn edge information. Step 3 uses the SGC model to aggregate node information. Step 4 uses MLP to predict miRNA-disease association score

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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