Predicting MicroRNA-Disease Associations Using Kronecker Regularized Least Squares Based on Heterogeneous Omics Data
MicroRNAs (miRNAs) play critical roles in many biological processes. Predicting the miRNA-disease associations will aid in deciphering the underlying pathogenesis of human polygenic diseases. However, existing in silico prediction methods typically utilize a single or limited data sources for diseas...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7862218/ |