期刊
SCIENTIFIC REPORTS
卷 6, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/srep36054
关键词
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资金
- Program for New Century Excellent Talents in university [NCET-10-0365]
- National Nature Science Foundation of China [60973082, 11171369, 61272395, 61370171]
- National Nature Science Foundation of Hunan Province [12JJ2041]
- Planned Science and Technology project of Hunan Province [2009FJ3195, 2012FJ1012]
- Fundamental Research Funds for Central universities, Hunan university
Prediction and confirmation of the presence of disease-related miRNAs is beneficial to understand disease mechanisms at the miRNA level. However, the use of experimental verification to identify disease-related miRNAs is expensive and time-consuming. Effective computational approaches used to predict miRNA-disease associations are highly specific. In this study, we develop the Network Consistency Projection for miRNA-Disease Associations (NCPMDA) method to reveal the potential associations between miRNAs and diseases. NCPMDA is a non-parametric universal network-based method that can simultaneously predict miRNA-disease associations in all diseases but does not require negative samples. NCPMDA can also confirm the presence of miRNAs in isolated diseases (diseases without any known miRNA association). Leave-one-out cross validation and case studies have shown that the predictive performance of NCPMDA is superior over that of previous method.
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