共 27 条
An Analysis of Human MicroRNA and Disease Associations
被引:730
作者:

Lu, Ming
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Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Zhang, Qipeng
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机构:
Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Deng, Min
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h-index: 0
机构:
Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Miao, Jing
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机构:
Peking Univ First Hosp, Dept Pediat, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Guo, Yanhong
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机构:
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Gao, Wei
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h-index: 0
机构:
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China

Cui, Qinghua
论文数: 0 引用数: 0
h-index: 0
机构:
Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
机构:
[1] Peking Univ, Hlth Sci Ctr, Dept Med Informat, Beijing 100871, Peoples R China
[2] Peking Univ, Minist Ed Key Lab Mol Cardiol, Beijing, Peoples R China
[3] Peking Univ First Hosp, Dept Pediat, Beijing, Peoples R China
来源:
PLOS ONE
|
2008年
/
3卷
/
10期
关键词:
D O I:
10.1371/journal.pone.0003420
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
It has been reported that increasingly microRNAs are associated with diseases. However, the patterns among the microRNA-disease associations remain largely unclear. In this study, in order to dissect the patterns of microRNA-disease associations, we performed a comprehensive analysis to the human microRNA-disease association data, which is manually collected from publications. We built a human microRNA associated disease network. Interestingly, microRNAs tend to show similar or different dysfunctional evidences for the similar or different disease clusters, respectively. A negative correlation between the tissue-specificity of a microRNA and the number of diseases it associated was uncovered. Furthermore, we observed an association between microRNA conservation and disease. Finally, we uncovered that microRNAs associated with the same disease tend to emerge as predefined microRNA groups. These findings can not only provide help in understanding the associations between microRNAs and human diseases but also suggest a new way to identify novel disease-associated microRNAs.
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