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Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model
BACKGROUND: Many studies prove that miRNAs have significant roles in diagnosing and treating complex human diseases. However, conventional biological experiments are too costly and time-consuming to identify unconfirmed miRNA-disease associations. Thus, computational models predicting unidentified m...
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| I publikationen: | BMC Bioinformatics |
|---|---|
| Huvudupphovsmän: | , , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
BioMed Central
2020
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7579830/ https://ncbi.nlm.nih.gov/pubmed/33087064 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-03765-2 |
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