Pei Liu

LaCONIC improves cancer survival prediction by integrating multi-omics data with gene regulatory networks and cancer subtypes, achieving better performance and interpretability.

ConvNTC predicts disease-related miRNA pairs and cell-related drug pairs by modeling triplet network connections with a novel convolutional neural tensor completion approach.

MiRGraph identifies microRNA-target interactions by integrating sequence and regulatory network data, outperforming existing methods in prediction accuracy and strength estimation.