Chapter title |
Computational Inferring of Risk Subpathways Mediated by Dysfunctional Non-coding RNAs
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Chapter number | 9 |
Book title |
Non-coding RNAs in Complex Diseases
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Published in |
Advances in experimental medicine and biology, September 2018
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DOI | 10.1007/978-981-13-0719-5_9 |
Pubmed ID | |
Book ISBNs |
978-9-81-130718-8, 978-9-81-130719-5
|
Authors |
Yanjun Xu, Yunpeng Zhang, Xia Li, Xu, Yanjun, Zhang, Yunpeng, Li, Xia |
Abstract |
Non-coding RNAs mediated core elements of pathways contributes to the disorder of biological function in diseases. Identification of non-coding RNAs mediated subpathways not only can help for deciphering the pathogenic mechanism of complex diseases, but also can gain insight into the functional roles of non-coding RNAs in human diseases. Here, we summarized the general steps for identifying non-coding RNA mediated subpathways and overviewed two of our previously developed methods, Subpathway-GMir and Subpathway-LNCE, which were designed to identify miRNAs and lncRNAs mediated risk subpathways respectively. We identified the key subpathway regions by integrating non-coding RNA-target gene associations, interesting genes and non-coding RNAs and pathway topologies. By applying methods to several disease datasets, we confirmed that our methods is effective in identifying risk subpathways and also can help uncover key non-coding RNAs in diseases. Additionally, reproducibility and robustness analysis demonstrated our methods are reliable. |
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Student > Bachelor | 1 | 100% |
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Neuroscience | 1 | 100% |