A novel computational method for the identification of potential mirna-disease association based on symmetric non-negative matrix factorization and kronecker regularized least square

HIGHLIGHTS

• who: Xing Chen from the School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China have published the research: A Novel Computational Method for the Identification of Potential miRNA-Disease Association Based on Symmetric Non-negative Matrix Factorization and Kronecker Regularized Least Square, in the Journal: (JOURNAL)
• what: The authors applied SNMFMDA to perform the third case study on LN to test the prediction power of the model when it is applied to another database HMDD v1.0. The authors developed a novel model of SNMFMDA to reveal the relation of . . .
  

   

  

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