| Chapter title |
Prediction of Non-coding RNAs as Drug Targets
|
|---|---|
| Chapter number | 11 |
| Book title |
Non-coding RNAs in Complex Diseases
|
| Published in |
Advances in experimental medicine and biology, September 2018
|
| DOI | 10.1007/978-981-13-0719-5_11 |
| Pubmed ID | |
| Book ISBNs |
978-9-81-130718-8, 978-9-81-130719-5
|
| Authors |
Wei Jiang, Yingli Lv, Shuyuan Wang, Jiang, Wei, Lv, Yingli, Wang, Shuyuan |
| Abstract |
MiRNA is a class of small non-coding RNA molecule that regulates gene expression at post-transcriptional level. Increasing evidences show aberrant expression of miRNAs in a variety of diseases. Targeting the dysregulated miRNAs with small molecule drugs has become a novel therapeutics for many human diseases, especially cancers. In this chapter, we introduced a series of computational studies for prediction of small molecule and miRNA associations. Based on different hypotheses, such as transcriptional response similarity, functional consistence or network closeness, the small molecule-miRNA networks were constructed and further analyzed. In addition, several resources that collected experimentally validated relationships or computational predicted associations between small molecules and miRNAs were provided. Collectively, these computational frameworks and databases pave a new way for miRNA-targeted therapy and drug repositioning. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 5 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 20% |
| Professor > Associate Professor | 1 | 20% |
| Researcher | 1 | 20% |
| Unknown | 2 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 20% |
| Chemistry | 1 | 20% |
| Medicine and Dentistry | 1 | 20% |
| Unknown | 2 | 40% |