Relation-Aware Heterogeneous Graph Learning for miRNA-Drug Response Association Prediction Under Cold-Start Generalization

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Background

Cancer drug resistance can be influenced by microRNAs (miRNAs), which can alter gene expression and cellular pathways that determine how cancer cells respond to treatment. Potential miRNA-drug response associations can be identified using computational models; however, evaluating these models using edge-based evaluation can result in an optimistic view of model generalization since test miRNAs or drugs can appear in other response associations during training. (2)