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学科主题: 基础医学
题名:
An upstream interacting context based framework for the computational inference of microRNA functions
作者: Qiu, Chengxiang1; Wang, Dong1; Wang, Edwin2; Cui, Qinghua1,3,4
刊名: MOLECULAR BIOSYSTEMS
发表日期: 2012
DOI: 10.1039/c2mb05469h
卷: 8, 期:5, 页:1492-1498
收录类别: SCI
文章类型: Article
WOS标题词: Science & Technology
类目[WOS]: Biochemistry & Molecular Biology
研究领域[WOS]: Biochemistry & Molecular Biology
关键词[WOS]: TRANSCRIPTION FACTOR ; REGULATORY NETWORK ; HUMAN-DISEASE ; EXPRESSION ; MOUSE ; PATHWAYS ; MIR-16 ; CANCER ; CELLS ; TOOL
英文摘要:

With the rapid accumulation of microRNA (miRNAs), a class of newly identified small noncoding RNAs, in silico inference of miRNA functions has become one of the central tasks in miRNA bioinformatics. Traditional methods have helped in the understanding of miRNAs, but they also have limitations. In this paper, we first gave a brief review for the progress of bioinformatic methods in miRNA function inference and next presented a new framework (miRUPnet) for inferring the functions of miRNAs by functional analysis of a novel dimension of miRNA network, the context of its transcription factors (TFs) in a protein-protein interaction network. This dimension represents specific biological processes initiated by TF combinations and therefore differs from traditional methods in concept. To validate the accuracy of our method, we first comprehensively mined literature-reported miRNA functions and then made a comparison with the prediction result. The results show that even using the stringent TFBS rule, our method has independently predicted 68.2% of the literature reported miRNA functions, suggesting that miRUPnet has a high accuracy. Moreover, our approach successfully predicted specific functions that could not be inferred for given miRNAs using traditional methods. More importantly, it can distinguish miRNAs from the same family, as well as those present in multiple copies that cannot be differentiated through traditional methods. This study presents a new concept and dimension for miRNA function inference. miRUPnet represents an important and novel method for inferring the function of miRNAs. miRUPnet is available at http://cmbi.bjmu.edu.cn/mirupnet.

语种: 英语
所属项目编号: 30900829
项目资助者: Natural Science Foundation of China
WOS记录号: WOS:000302368600014
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.bjmu.edu.cn/handle/400002259/67710
Appears in Collections:基础医学院_北京大学系统生物医学研究所_期刊论文

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作者单位: 1.Sch Basic Med Sci, Dept Biomed Informat, Beijing 100191, Peoples R China
2.Peking Univ, Inst Syst Biomed, Beijing 100191, Peoples R China
3.Natl Res Council Canada, Biotechnol Res Inst, Montreal, PQ H4P 2R2, Canada
4.Peking Univ, MOE Key Lab Mol Cardiovasc Sci, Beijing 100191, Peoples R China

Recommended Citation:
Qiu, Chengxiang,Wang, Dong,Wang, Edwin,et al. An upstream interacting context based framework for the computational inference of microRNA functions[J]. MOLECULAR BIOSYSTEMS,2012,8(5):1492-1498.
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