Name
Title | ||
|---|---|---|
Adversarial Dual-Channel Variational Graph Autoencoder for Synthetic Lethality Prediction in Human Cancers |
Abstract | ||
|---|---|---|
Synthetic Lethality (SL) is a type of vital gene interaction that can lead to various human diseases including cancers. Therefore, SL gene pair prediction can aid in the prevention and treatment of cancer. A number of computational approaches, especially Graph Neural Network (GNN) based methods, have been proposed for this link prediction problem on the graph. However, these GNN-based methods only... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/BIBM52615.2021.9669763 | 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) |
Keywords | DocType | ISBN |
Conferences,Biological system modeling,Gaussian distribution,Predictive models,Graph neural networks,Random variables,Bioinformatics | Conference | 978-1-6654-0126-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Li | 1 | 0 | 0.34 |
| Han Zhang | 2 | 7 | 5.29 |
| Qingqing Zhao | 3 | 0 | 0.68 |
| Jian Liu | 4 | 0 | 0.34 |
| Yanbin Yin | 5 | 31 | 7.75 |