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LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction
Predicting novel microRNA (miRNA)-disease associations is clinically significant due to miRNAs’ potential roles of diagnostic biomarkers and therapeutic targets for various human diseases. Previous studies have demonstrated the viability of utilizing different types of biological data to computation...
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| 出版年: | PLoS Comput Biol |
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| 主要な著者: | , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5749861/ https://ncbi.nlm.nih.gov/pubmed/29253885 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1005912 |
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