中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
An Improved Method for Identification of Pre-miRNA in Drosophila

文献类型:期刊论文

作者Yu, Tieying; Chen, Min; Wang, Chunde
刊名IEEE ACCESS
出版日期2020
卷号8页码:52173-52180
关键词MICRORNA-DISEASE ASSOCIATIONS IDENTIFYING PROMOTERS GENE-EXPRESSION PREDICTION RNA SITES DNA METHYLATION DATABASE NETWORK
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
文献子类Article
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.
WOS关键词MICRORNA-DISEASE ASSOCIATIONS ; IDENTIFYING PROMOTERS ; GENE-EXPRESSION ; PREDICTION ; RNA ; SITES ; DNA ; METHYLATION ; DATABASE ; NETWORK
语种英语
WOS记录号WOS:000524748500085
资助机构Natural Science Foundation of ChinaNational Natural Science Foundation of China [31572618, 31972791]
源URL[http://ir.yic.ac.cn/handle/133337/25098]  
专题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.Qingdao Agr Univ, Marine Sci & Engn Coll, Qingdao 266109, Peoples R China
2.Shandong Agr Univ, Coll Life Sci, Tai An 271018, Shandong, Peoples R China;
3.Chinese Acad Sci, Ctr Ocean Mega Sci, Yantai 264003, Peoples R China;
4.Chinese Acad Sci, Yantai Inst Coastal Zone Res, Yantai 264003, Peoples R China;
推荐引用方式
GB/T 7714
Yu, Tieying,Chen, Min,Wang, Chunde. An Improved Method for Identification of Pre-miRNA in Drosophila[J]. IEEE ACCESS,2020,8:52173-52180.
APA Yu, Tieying,Chen, Min,&Wang, Chunde.(2020).An Improved Method for Identification of Pre-miRNA in Drosophila.IEEE ACCESS,8,52173-52180.
MLA Yu, Tieying,et al."An Improved Method for Identification of Pre-miRNA in Drosophila".IEEE ACCESS 8(2020):52173-52180.

入库方式: OAI收割

来源:烟台海岸带研究所

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