IR@PKUHSC  > 北京大学基础医学院  > 医学信息学系
学科主题医学信息学
Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier
Chen, Xing1,2; Liu, Ming-Xi2,3; Cui, Qing-Hua4; Yan, Gui-Ying1,2
刊名PLOS ONE
2012-08-24
DOI10.1371/journal.pone.0043425
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
WOS记录号WOS:000308225500050
项目编号10531070 ; 10721101 ; KJCX-YW-S7
资助机构National Natural Science of Foundation of China ; NCMIS
引用统计
被引频次:37[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/64550
专题北京大学基础医学院_医学信息学系
北京大学基础医学院
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
推荐引用方式
GB/T 7714
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).
APA Chen, Xing,Liu, Ming-Xi,Cui, Qing-Hua,&Yan, Gui-Ying.(2012).Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier.PLOS ONE,7(8).
MLA Chen, Xing,et al."Prediction of Disease-Related Interactions between MicroRNAs and Environmental Factors Based on a Semi-Supervised Classifier".PLOS ONE 7.8(2012).
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