Mining featured patterns of MiRNA interaction based on sequence and structure similarity.
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.
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China.
Qingfeng
Q
Chen
Wei
W
Lan
Jianxin
J
Wang
D000465:Algorithms; D000818:Animals; D000852:Anopheles; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining; D030541:Databases, Genetic; D004331:Drosophila melanogaster; D019277:Entropy; D053263:Gene Regulatory Networks; D017344:Genes, Insect; D035683:MicroRNAs / Q000737:chemistry* / Q000235:genetics* / Q000378:metabolism; D009690:Nucleic Acid Conformation; D013045:Species Specificity
D035683:MicroRNAs