Prediction of plant-derived xenomiRs from plant miRNA sequences using random forest and one-dimensional convolutional neural network models.

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作者： Qi,Zhao ^[1] ; Qian,Mao ^[2] ; Zheng,Zhao ^[3] ; Tongyi,Dou ^[4] ; Zhiguo,Wang ^[1] ; Xiaoyu,Cui ^[5] ; Yuanning,Liu ^[1] ; Xiaoya,Fan ^[6]

作者单位： Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110169, Liaoning, China. ^[1] Light Industry College, Liaoning University, Shenyang, 110036, Liaoning, China. ^[2] Department of Network Engineering, Zhengzhou Science and Technology Institute, Zhengzhou, 450000, Henan, China. ^[3] School of Life Science and Medicine, Dalian University of Technology, Panjin, 124221, China. ^[4] Department of Nuclear Medicine, The General Hospital of Shenyang Military Area Command, Shenyang, 110840, China. ^[5] Computer Science and Technology College, Jilin University, Changchun, 130012, China. ^[6] Bio-, Electro- And Mechanical Systems, Université Libre de Bruxelles, Avenue F.D. Roosevelt 50 CP165/56, 1050, Brussels, Belgium. xiaoya.fan@ulb.ac.be. ^[7]

关键词 Cross-kingdom regulation Machine learning Plant-derived xenomiR Selective absorption Statistics analysis miRNA

主题词数据库, 核酸(Databases, Nucleic Acid);高通量核苷酸序列分析(High-Throughput Nucleotide Sequencing);人类(Humans);微RNAs(MicroRNAs);植物(Plants);RNA, 植物(RNA, Plant)

DOI 10.1186/s12864-018-5227-3

PMID 30477446

发布时间 2019-12-10

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