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Non-coding RNAs in Complex Diseases

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Attention for Chapter 9: Computational Inferring of Risk Subpathways Mediated by Dysfunctional Non-coding RNAs
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Chapter title
Computational Inferring of Risk Subpathways Mediated by Dysfunctional Non-coding RNAs
Chapter number 9
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_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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Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 100%
Readers by discipline Count As %
Neuroscience 1 100%