Name
Title | ||
|---|---|---|
A multi-task graph convolutional network modeling of drug-drug interactions and synergistic efficacy |
Abstract | ||
|---|---|---|
Identification of drug-drug interaction(DDI) is critical for safer and more effective drug co-prescription. As wetlab screening assays are time-consuming, labor-intensive and expensive, it is highly desired to develop an effective computational method to predict drug-drug interactions. In this work, we aim to predict of drug-drug interactions and synergistic drug combinations by proposing an end-t... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/BIBM52615.2021.9669575 | 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) |
Keywords | DocType | ISBN |
Drugs,Support vector machines,Radio frequency,Performance evaluation,Conferences,Machine learning,Predictive models | Conference | 978-1-6654-0126-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuanyuan Deng | 1 | 1 | 1.02 |
| Song Yu | 2 | 0 | 1.35 |
| Lei Deng | 3 | 63 | 15.72 |
| Hui Liu | 4 | 0 | 0.34 |
| Xuejun Liu | 5 | 0 | 1.35 |
| Yi Luo | 6 | 0 | 0.34 |