A Novel Computational Method for the Identification of Potential miRNA-Disease Association Based on Symmetric Non-negative Matrix Factorization and Kronecker Regularized Least Square

Podobne zapisy

• SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association
  od: Zhao, Yan, i wsp.
  Wydane: (2019)
• MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA–disease association prediction
  od: Xing Chen, i wsp.
  Wydane: (2017-12-01)
• MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA–disease association prediction
  od: Chen, Xing, i wsp.
  Wydane: (2017)
• MDAKRLS: Predicting human microbe-disease association based on Kronecker regularized least squares and similarities
  od: Xu, Da, i wsp.
  Wydane: (2021)
• Kinase Identification with Supervised Laplacian Regularized Least Squares.
  od: Ao Li, i wsp.
  Wydane: (2015-01-01)