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Mining Featured Patterns of MiRNA Interaction Based on Sequence and Structure Similarity
March-April 2013 (vol. 10 no. 2)
pp. 415-422
Qingfeng Chen, Guangxi University, Nanning
Wei Lan, Guangxi University, Nanning
Jianxin Wang, Central South University, Changsha
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.
Index Terms:
Entropy,Joints,RNA,Educational institutions,Databases,Computational biology,joint entropy,Entropy,Joints,RNA,Educational institutions,Databases,Computational biology,interaction,Structure,similarity,miRNA
Citation:
Qingfeng Chen, Wei Lan, Jianxin Wang, "Mining Featured Patterns of MiRNA Interaction Based on Sequence and Structure Similarity," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 2, pp. 415-422, March-April 2013, doi:10.1109/TCBB.2013.5
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