NDLI: Mining Featured Patterns of MiRNA Interaction Based on Sequence and Structure Similarity

Content Provider	ACM Digital Library
Author	Chen, Qingfeng Lan, Wei Wang, Jianxin
Abstract	MicroRNA (miRNA) is an endogenous small noncoding RNA that plays an important role in gene expression through the post-transcriptional gene regulation pathways. There are many literature works focusing on predicting miRNA targets and exploring gene regulatory networks of miRNA families. We suggest, however, the study to identify the interaction between miRNAs is insufficient. This paper presents a framework to identify relationships between miRNAs using joint entropy, to investigate the regulatory features of miRNAs. Both the sequence and secondary structure are taken into consideration to make our method more relevant from the biological viewpoint. Further, joint entropy is applied to identify correlated miRNAs, which are more desirable from the perspective of the gene regulatory network. A data set including Drosophila melanogaster and Anopheles gambiae is used in the experiment. The results demonstrate that our approach is able to identify known miRNA interaction and uncover novel patterns of miRNA regulatory network.
Starting Page	415
Ending Page	422
Page Count	8
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2013.5
Volume Number	10
Issue Number	2
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-03-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Entropy,Joints,RNA,Educational institutions,Databases,Computational biology,joint entropy,Entropy,Joints,RNA,Educational institutions,Databases,Computational biology,interaction,Structure,similarity,miRNA
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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