【摘要】 miRNA与其靶基因的作用机制十分复杂,因此,miRNA靶基因识别问题一直是miRNA研究领域的热点难题。该文基于CLASH数据集,提出了miRNA-靶位点配对序列特征,并使用随机森林建模。实验结果表明,本模型的Acc,Sen,Spe,Pre以及Mcc分别达到90.05%,89.47%,90.56%,90.43%和0.799 8;ROC和PRC的AUC分别为0.954,0.958。相比已有方法,该方法表现出更加良好的性能,说明新引入的miRNA-靶位点配对序列特征对miRNA靶基因识别有很重大的影响。更多还原

【Abstract】 The mechanisms underlying the interaction of miRNAs with their mRNA targets are quite complex,which makes miRNA target prediction be a hot issue in the field of miRNA research. The features of miRNA-target sites pairing sequences were proposed based on the CLASH dataset,and the random forest models were applied for modeling. The average values of Acc,Sen,Spe,Pre and Mcc are 90. 05%,89. 47%,90. 56%,90. 43% and 0. 799 8,respectively,and the AUC of ROC and PRC are 0. 954 and 0. 958,respectively. The results indicated that the current method shows a better performance compared with the existed methods,and the features newly constructed have a very significant impact on the identification of miRNA target genes.更多还原