Publications by authors named "Zheming Xing"
circ2DGNN: circRNA-disease Association Prediction via Transformer-based Graph Neural Network.
IEEE/ACM Trans Comput Biol Bioinform
October 2024
Article Synopsis
- Investigating the links between circular RNAs (circRNAs) and diseases is essential for understanding disease mechanisms and developing better therapies, but existing methods only consider known data, missing vital interactions with other biomolecules.
- To overcome these limitations, researchers created circ2DGNN, a new computational model that uses a heterogeneous network to analyze the relationships between circRNAs, diseases, and other biomolecules more comprehensively.
- circ2DGNN employs advanced graph representation learning techniques, including a Transformer-like architecture, to improve predictions and has been shown to outperform current leading models in evaluations.