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学科主题: 医学信息学
题名:
Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier
作者: Chen, Xing1,2; Liu, Ming-Xi2,3; Cui, Qing-Hua4; Yan, Gui-Ying1,2
刊名: PLOS ONE
发表日期: 2012-08-24
DOI: 10.1371/journal.pone.0043425
卷: 7, 期:8
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Multidisciplinary Sciences
研究领域[WOS]: Science & Technology - Other Topics
关键词[WOS]: DRUG-TARGET INTERACTION ; ARSENIC TRIOXIDE ; LIVER-DISEASE ; CANCER-CELLS ; EXPRESSION ; NETWORK ; APOPTOSIS ; PRIORITIZATION ; PATHOGENESIS ; SIMILARITY
英文摘要:

Accumulated evidence has shown that microRNAs (miRNAs) can functionally interact with a number of environmental factors (EFs) and their interactions critically affect phenotypes and diseases. Therefore, in-silico inference of disease-related miRNA-EF interactions is becoming crucial not only for the understanding of the mechanisms by which miRNAs and EFs contribute to disease, but also for disease diagnosis, treatment, and prognosis. In this paper, we analyzed the human miRNA-EF interaction data and revealed that miRNAs (EFs) with similar functions tend to interact with similar EFs (miRNAs) in the context of a given disease, which suggests a potential way to expand the current relation space of miRNAs, EFs, and diseases. Based on this observation, we further proposed a semi-supervised classifier based method (miREFScan) to predict novel disease-related interactions between miRNAs and EFs. As a result, the leave-one-out cross validation has shown that miREFScan obtained an AUC of 0.9564, indicating that miREFScan has a reliable performance. Moreover, we applied miREFScan to predict acute promyelocytic leukemia-related miRNA-EF interactions. The result shows that forty-nine of the top 1% predictions have been confirmed by experimental literature. In addition, using miREFScan we predicted and publicly released novel miRNA-EF interactions for 97 human diseases. Finally, we believe that miREFScan would be a useful bioinformatic resource for the research about the relationships among miRNAs, EFs, and human diseases.

语种: 英语
所属项目编号: 10531070 ; 10721101 ; KJCX-YW-S7
项目资助者: National Natural Science of Foundation of China ; NCMIS
WOS记录号: WOS:000308225500050
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/64550
Appears in Collections:基础医学院_医学信息学系_期刊论文

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作者单位: 1.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Grad Univ, Beijing, Peoples R China
4.Peking Univ, Dept Biomed Informat, Sch Basic Med Sci, Beijing 100871, Peoples R China

Recommended Citation:
Chen, Xing,Liu, Ming-Xi,Cui, Qing-Hua,et al. Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier[J]. PLOS ONE,2012,7(8).
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