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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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| Pubblicato in: | PLoS Comput Biol |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2017
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| Soggetti: | |
| Accesso online: | 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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