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• W2022732522 abstract "MicroRNAs play critical role in the development and progression of various diseases. Predicting potential miRNA-disease associations from vast amount of biological data is an important problem in the biomedical research. Considering the limitations in previous methods, we developed Regularized Least Squares for MiRNA-Disease Association (RLSMDA) to uncover the relationship between diseases and miRNAs. RLSMDA can work for diseases without known related miRNAs. Furthermore, it is a semi-supervised (does not need negative samples) and global method (prioritize associations for all the diseases simultaneously). Based on leave-one-out cross validation, reliable AUC have demonstrated the reliable performance of RLSMDA. We also applied RLSMDA to Hepatocellular cancer and Lung cancer and implemented global prediction for all the diseases simultaneously. As a result, 80% (Hepatocellular cancer) and 84% (Lung cancer) of top 50 predicted miRNAs and 75% of top 20 potential associations based on global prediction have been confirmed by biological experiments. We also applied RLSMDA to diseases without known related miRNAs in golden standard dataset. As a result, in the top 3 potential related miRNA list predicted by RLSMDA for 32 diseases, 34 disease-miRNA associations were successfully confirmed by experiments. It is anticipated that RLSMDA would be a useful bioinformatics resource for biomedical researches." @default.
• W2022732522 created "2016-06-24" @default.
• W2022732522 creator A5017998243 @default.
• W2022732522 creator A5033532580 @default.
• W2022732522 date "2014-06-30" @default.
• W2022732522 modified "2023-10-01" @default.
• W2022732522 title "Semi-supervised learning for potential human microRNA-disease associations inference" @default.
• W2022732522 cites W14098964 @default.
• W2022732522 cites W144423133 @default.
• W2022732522 cites W1514821037 @default.
• W2022732522 cites W1648301895 @default.
• W2022732522 cites W1667789979 @default.
• W2022732522 cites W1798188187 @default.
• W2022732522 cites W1920303762 @default.
• W2022732522 cites W1933460162 @default.
• W2022732522 cites W1941092849 @default.
• W2022732522 cites W1966607967 @default.
• W2022732522 cites W1967087625 @default.
• W2022732522 cites W1967539215 @default.
• W2022732522 cites W1969594222 @default.
• W2022732522 cites W1971588341 @default.
• W2022732522 cites W1974650935 @default.
• W2022732522 cites W1979828436 @default.
• W2022732522 cites W1983892570 @default.
• W2022732522 cites W1984936387 @default.
• W2022732522 cites W1984985728 @default.
• W2022732522 cites W1985707457 @default.
• W2022732522 cites W1988964743 @default.
• W2022732522 cites W1989454102 @default.
• W2022732522 cites W1990821116 @default.
• W2022732522 cites W1994061059 @default.
• W2022732522 cites W1997118916 @default.
• W2022732522 cites W1998484940 @default.
• W2022732522 cites W1999812198 @default.
• W2022732522 cites W2002995168 @default.
• W2022732522 cites W2008092800 @default.
• W2022732522 cites W2008297386 @default.
• W2022732522 cites W2010265726 @default.
• W2022732522 cites W2014946489 @default.
• W2022732522 cites W2026051181 @default.
• W2022732522 cites W2026570544 @default.
• W2022732522 cites W2027514285 @default.
• W2022732522 cites W2027762384 @default.
• W2022732522 cites W2039213901 @default.
• W2022732522 cites W2047967134 @default.
• W2022732522 cites W2057231053 @default.
• W2022732522 cites W2060913442 @default.
• W2022732522 cites W2071390582 @default.
• W2022732522 cites W2075263617 @default.
• W2022732522 cites W2075329854 @default.
• W2022732522 cites W2077751073 @default.
• W2022732522 cites W2078349873 @default.
• W2022732522 cites W2084400739 @default.
• W2022732522 cites W2085442947 @default.
• W2022732522 cites W2088797440 @default.
• W2022732522 cites W2089001345 @default.
• W2022732522 cites W2090335107 @default.
• W2022732522 cites W2092516659 @default.
• W2022732522 cites W2093992697 @default.
• W2022732522 cites W2098318517 @default.
• W2022732522 cites W2098392534 @default.
• W2022732522 cites W2106016477 @default.
• W2022732522 cites W2106029302 @default.
• W2022732522 cites W2112192177 @default.
• W2022732522 cites W2117391818 @default.
• W2022732522 cites W2118422217 @default.
• W2022732522 cites W2118814218 @default.
• W2022732522 cites W2119687825 @default.
• W2022732522 cites W2122211092 @default.
• W2022732522 cites W2122493934 @default.
• W2022732522 cites W2124499207 @default.
• W2022732522 cites W2125713917 @default.
• W2022732522 cites W2126619650 @default.
• W2022732522 cites W2128768066 @default.
• W2022732522 cites W2129158737 @default.
• W2022732522 cites W2130979840 @default.
• W2022732522 cites W2135433834 @default.
• W2022732522 cites W2135580384 @default.
• W2022732522 cites W2135613885 @default.
• W2022732522 cites W2135810600 @default.
• W2022732522 cites W2136037673 @default.
• W2022732522 cites W2137834254 @default.
• W2022732522 cites W2138664009 @default.
• W2022732522 cites W2141222510 @default.
• W2022732522 cites W2145361279 @default.
• W2022732522 cites W2146292498 @default.
• W2022732522 cites W2150536104 @default.
• W2022732522 cites W2151025094 @default.
• W2022732522 cites W2151519667 @default.
• W2022732522 cites W2151871253 @default.
• W2022732522 cites W2154551754 @default.
• W2022732522 cites W2159444732 @default.
• W2022732522 cites W2160505237 @default.
• W2022732522 cites W2162278418 @default.
• W2022732522 cites W2162674813 @default.
• W2022732522 cites W2164383394 @default.
• W2022732522 cites W2171232191 @default.
• W2022732522 cites W3103971085 @default.
• W2022732522 doi "https://doi.org/10.1038/srep05501" @default.
• W2022732522 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4074792" @default.

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