Name
Title | ||
|---|---|---|
Prediction of novel drugs for hepatocellular carcinoma based on multi-source random walk. |
Abstract | ||
|---|---|---|
Computational approaches for predicting drug-disease associations by integrating gene expression and biological network provide great insights to the complex relationships among drugs, targets, disease genes, and diseases at a system level. Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with a high rate of morbidity and mortality. We provide an integrative framework to p... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCBB.2016.2550453 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | Field | DocType |
Drugs,Diseases,Gene expression,Proteins,Electronic mail,Databases,Chemicals | Drug repositioning,Disease,Toxicogenomics,Hepatocellular carcinoma,Computer science,Biological network,Interaction network,Regorafenib,KEGG,Bioinformatics | Journal |
Volume | Issue | ISSN |
14 | 4 | 1545-5963 |
Citations | PageRank | References |
1 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Liang | 1 | 21 | 12.01 |
| Ruidan Su | 2 | 1 | 1.02 |
| Bingbo Wang | 3 | 5 | 3.87 |
| Long Zhang | 4 | 1 | 0.34 |
| Yapeng Zou | 5 | 1 | 0.34 |
| Jing Zhang | 6 | 1 | 2.03 |
| Lin Gao | 7 | 137 | 29.86 |