State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning 530004, China.
IEEE/ACM Trans Comput Biol Bioinform. 2013 Mar-Apr;10(2):415-22. doi: 10.1109/TCBB.2013.5.
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.
微小 RNA（miRNA）是一种内源性的小非编码 RNA，通过转录后基因调控途径在基因表达中发挥重要作用。有许多文献致力于预测 miRNA 靶标和探索 miRNA 家族的基因调控网络。然而，我们认为，miRNA 之间相互作用的研究还不够充分。本文提出了一种使用联合熵识别 miRNA 之间关系的框架，以研究 miRNA 的调控特征。我们的方法同时考虑了 miRNA 的序列和二级结构，使其从生物学角度更具相关性。此外，联合熵还可用于识别相关 miRNA，从基因调控网络的角度来看，这更具可取性。实验中使用了一个包含果蝇和疟蚊的数据集。结果表明，我们的方法能够识别已知的 miRNA 相互作用，并揭示 miRNA 调控网络的新规律。
