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• W2890728516 abstract "The development and progression of numerous complex human diseases have been confirmed to be associated with microRNAs (miRNAs) by various experimental and clinical studies. Predicting potential miRNA-disease associations can help us understand the underlying molecular and cellular mechanisms of diseases and promote the development of disease treatment and diagnosis. Due to the high cost of conventional experimental verification, proposing a new computational method for miRNA-disease association prediction is an efficient and economical way. Since previous computational models ignored the hubness phenomenon, we presented a novel computational model of Bipartite Local models and Hubness-Aware Regression for MiRNA-Disease Association prediction (BLHARMDA). In this method, we first used known miRNA-disease associations to calculate the Jaccard similarity between miRNAs and between diseases, then utilized a modified kNNs model in the bipartite local model method. As a result, we effectively alleviated the detriments from 'bad' hubs. BLHARMDA obtained AUCs of 0.9141 and 0.8390 in the global and local leave-one-out cross validation, respectively, which outperformed most of the previous models and proved high prediction performance of BLHARMDA. Besides, the standard deviation of 0.0006 in 5-fold cross validation confirmed our model's prediction stability and the averaged prediction accuracy of 0.9120 showed the high precision of our model. In addition, to further evaluate our model's accuracy, we implemented BLHARMDA on three typical human diseases in three different types of case studies. As a result, 49 (Esophageal Neoplasms), 50 (Lung Neoplasms) and 50 (Carcinoma Hepatocellular) out of the top 50 related miRNAs were validated by recent experimental discoveries." @default.
• W2890728516 created "2018-09-27" @default.
• W2890728516 creator A5024439005 @default.
• W2890728516 creator A5033532580 @default.
• W2890728516 creator A5040628447 @default.
• W2890728516 date "2018-09-02" @default.
• W2890728516 modified "2023-10-12" @default.
• W2890728516 title "Predicting microRNA-disease associations using bipartite local models and hubness-aware regression" @default.
• W2890728516 cites W1158178075 @default.
• W2890728516 cites W14098964 @default.
• W2890728516 cites W1436642346 @default.
• W2890728516 cites W144423133 @default.
• W2890728516 cites W1521652389 @default.
• W2890728516 cites W1648301895 @default.
• W2890728516 cites W1667789979 @default.
• W2890728516 cites W1967087625 @default.
• W2890728516 cites W1971529620 @default.
• W2890728516 cites W1975933233 @default.
• W2890728516 cites W1979538859 @default.
• W2890728516 cites W1987360584 @default.
• W2890728516 cites W1989454102 @default.
• W2890728516 cites W2002938531 @default.
• W2890728516 cites W2002995168 @default.
• W2890728516 cites W2006797972 @default.
• W2890728516 cites W2014946489 @default.
• W2890728516 cites W2017426710 @default.
• W2890728516 cites W2019257830 @default.
• W2890728516 cites W2022732522 @default.
• W2890728516 cites W2023827592 @default.
• W2890728516 cites W2027514285 @default.
• W2890728516 cites W2032298477 @default.
• W2890728516 cites W2040935952 @default.
• W2890728516 cites W2047967134 @default.
• W2890728516 cites W2058220018 @default.
• W2890728516 cites W2059267594 @default.
• W2890728516 cites W2061641806 @default.
• W2890728516 cites W2070448217 @default.
• W2890728516 cites W2070571588 @default.
• W2890728516 cites W2084645564 @default.
• W2890728516 cites W2090335107 @default.
• W2890728516 cites W2092193862 @default.
• W2890728516 cites W2098318517 @default.
• W2890728516 cites W2102523936 @default.
• W2890728516 cites W2106029302 @default.
• W2890728516 cites W2109555487 @default.
• W2890728516 cites W2111112354 @default.
• W2890728516 cites W2112192177 @default.
• W2890728516 cites W2118546156 @default.
• W2890728516 cites W2122211092 @default.
• W2890728516 cites W2124756133 @default.
• W2890728516 cites W2126619650 @default.
• W2890728516 cites W2128768066 @default.
• W2890728516 cites W2129158737 @default.
• W2890728516 cites W2132694427 @default.
• W2890728516 cites W2136037673 @default.
• W2890728516 cites W2136068960 @default.
• W2890728516 cites W2138664009 @default.
• W2890728516 cites W2139736926 @default.
• W2890728516 cites W2141222510 @default.
• W2890728516 cites W2142937131 @default.
• W2890728516 cites W2146236962 @default.
• W2890728516 cites W2150203365 @default.
• W2890728516 cites W2151025094 @default.
• W2890728516 cites W2152970345 @default.
• W2890728516 cites W2154551754 @default.
• W2890728516 cites W2155566653 @default.
• W2890728516 cites W2158135353 @default.
• W2890728516 cites W2158734599 @default.
• W2890728516 cites W2160467221 @default.
• W2890728516 cites W2161817637 @default.
• W2890728516 cites W2162674813 @default.
• W2890728516 cites W2163578933 @default.
• W2890728516 cites W2167179802 @default.
• W2890728516 cites W2171232191 @default.
• W2890728516 cites W2181996424 @default.
• W2890728516 cites W2321119966 @default.
• W2890728516 cites W2408796111 @default.
• W2890728516 cites W2410390867 @default.
• W2890728516 cites W2416873003 @default.
• W2890728516 cites W2511620854 @default.
• W2890728516 cites W2584926544 @default.
• W2890728516 cites W2597632520 @default.
• W2890728516 cites W2598821379 @default.
• W2890728516 cites W2601934706 @default.
• W2890728516 cites W2607159126 @default.
• W2890728516 cites W2765950793 @default.
• W2890728516 cites W2780777007 @default.
• W2890728516 cites W2799307902 @default.
• W2890728516 cites W2809363952 @default.
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• W2890728516 cites W611910056 @default.
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• W2890728516 doi "https://doi.org/10.1080/15476286.2018.1517010" @default.
• W2890728516 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6284580" @default.
• W2890728516 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30196756" @default.
• W2890728516 hasPublicationYear "2018" @default.
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