An Improved Method for Identification of Pre-miRNA in Drosophila
Yu, Tieying; Chen, Min; Wang, Chunde
发表期刊IEEE ACCESS
2020
卷号8页码:52173-52180
关键词MICRORNA-DISEASE ASSOCIATIONSIDENTIFYING PROMOTERSGENE-EXPRESSIONPREDICTIONRNASITESDNAMETHYLATIONDATABASENETWORK
研究领域Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications
DOI10.1109/ACCESS.2020.2980897
产权排序[Yu, Tieying; Chen, Min; Wang, Chunde] Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China; [Yu, Tieying; Chen, Min; Wang, Chunde] Chinese Acad Sci, Ctr Ocean Mega Sci, Yantai 264003, Peoples R China; [Yu, Tieying] Shandong Agr Univ, Coll Life Sci, Tai An 271018, Shandong, Peoples R China; [Wang, Chunde] Qingdao Agr Univ, Marine Sci & Engn Coll, Qingdao 266109, Peoples R China
作者部门海岸带生物资源高效利用研究与发展中心
英文摘要Identification of microRNAs is important in studies of regulation of gene expression in many biologyical processes. In this study, we developed an improved method for identification of microRNAs in Drosophila. We used the iLearn, PyFeat, and Pse-in-One methods to extract the features and then used Max-Relevance-Max-Distance (MRMD2.0) and t-Distributed Stochastic Neighbour Embedding (t-SNE) to reduce dimension of the features and the random forest classifier in Weka to identify miRNAs. With this method, we found that the discriminative features for identification of pre-miRNAs were, in Drosophila melanogaster, the occurrences of G & x005F;GUG and C & x005F;AGU when the value of the feature vector was greater than 2, and in Drosophila pseudoobscura, the 4-tuple nucleotide composition and the occurrence of 4-length neighbouring nucleic acids when the value of the feature vector was less than 0.02. These vectors covered all compositional information or the frequency of bases. Classification results showed the classification accuracy was 95.7 & x0025; and 93.6 & x0025;, the precision rate was 95.8 & x0025; and 93.6 & x0025;, and the recall rate was 95.7 & x0025; and 93.6 & x0025; in Drosophila melanogaster and Drosophila pseudoobscura, respectively, which are higher than those reported in previous studies.
文章类型Article
资助机构Natural Science Foundation of ChinaNational Natural Science Foundation of China [31572618, 31972791]
收录类别SCI
语种英语
关键词[WOS]MICRORNA-DISEASE ASSOCIATIONS; IDENTIFYING PROMOTERS; GENE-EXPRESSION; PREDICTION; RNA; SITES; DNA; METHYLATION; DATABASE; NETWORK
WOS记录号WOS:000524748500085
引用统计
文献类型期刊论文
条目标识符http://ir.yic.ac.cnhttp://ir.yic.ac.cn/handle/133337/25098
专题海岸带生物学与生物资源利用重点实验室_海岸带生物资源高效利用研究与发展中心
中国科学院烟台海岸带研究所

作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China;
2.Chinese Acad Sci, Ctr Ocean Mega Sci, Yantai 264003, Peoples R China;
3.Shandong Agr Univ, Coll Life Sci, Tai An 271018, Shandong, Peoples R China;
4.Qingdao Agr Univ, Marine Sci & Engn Coll, Qingdao 266109, Peoples R China

推荐引用方式
GB/T 7714Yu, Tieying,Chen, Min,Wang, Chunde. An Improved Method for Identification of Pre-miRNA in Drosophila[J]. IEEE ACCESS,2020,8:52173-52180.
APAYu, Tieying,Chen, Min,&Wang, Chunde.(2020).An Improved Method for Identification of Pre-miRNA in Drosophila.IEEE ACCESS,8,52173-52180.
MLAYu, Tieying,et al."An Improved Method for Identification of Pre-miRNA in Drosophila".IEEE ACCESS 8(2020):52173-52180.


PDF全文下载地址:

点我下载PDF