Name
Title | ||
|---|---|---|
On predicting epithelial mesenchymal transition by integrating RNA-binding proteins and correlation data via L 1/2 -regularization method. |
Abstract | ||
|---|---|---|
•We proposed a model for identifying the important RBPs during epithelial-mesenchymal transition (EMT).•L1/2-regularization model as a feature selector extends the model of LASSO.•L1/2-regularization model is successfully applied for identifying significant RBPs in biological researches.•The identified RBPs will facilitate biologists to study the underlying mechanism of EMT. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.artmed.2018.09.005 | Artificial Intelligence in Medicine |
Keywords | DocType | Volume |
L1/2-regularization,Classification,RNA-binding proteins (RBPs),Epithelial-mesenchymal transition (EMT) | Journal | 95 |
ISSN | Citations | PageRank |
0933-3657 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yushan Qiu | 1 | 20 | 6.28 |
| Hao Jiang | 2 | 22 | 8.41 |
| Wai-Ki Ching | 3 | 683 | 78.66 |
| Ng Michael | 4 | 4231 | 311.70 |