MNESEDA: A prior-guided subgraph representation learning framework for predicting disease-related enhancers
Article in Knowledge-Based Systems (June 2024)
The most recent citing publications are shown below. View all 21 publications that cite this research output on Dimensions.
Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer
Preprint in bioRxiv (April 2024)
AMPFLDAP: Adaptive Message Passing and Feature Fusion on Heterogeneous Network for LncRNA-Disease Associations Prediction
Article in Interdisciplinary Sciences: Computational Life Sciences (April 2024)