Name
Abstract | ||
|---|---|---|
The discovery of human disease-related miRNA isa challenging problem for complex disease biology research. For existing computational methods, it is difficult to achieve excellent performance with sparse known miRNA-disease association verified by biological experiment. Here, we develop CPTL, a Collective Prediction based on Transduction Learning, to systematically prioritize miRNAs related to dis... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCBB.2016.2599866 | IEEE/ACM Transactions on Computational Biology and Bioinformatics |
Keywords | Field | DocType |
Predictive models,Convergence,Breast cancer,Learning systems | Convergence (routing),Disease,Computer science,Artificial intelligence,Bioinformatics,Transduction (genetics),Machine learning,Network structure | Journal |
Volume | Issue | ISSN |
14 | 6 | 1545-5963 |
Citations | PageRank | References |
9 | 0.51 | 13 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiawei Luo | 1 | 66 | 10.72 |
| Pingjian Ding | 2 | 20 | 4.13 |
| Cheng Liang | 3 | 60 | 9.31 |
| Buwen Cao | 4 | 26 | 3.25 |
| Xiangtao Chen | 5 | 20 | 4.07 |