AMCSMMA: Predicting Small Molecule-miRNA Potential Associations Based on Accurate Matrix Completion.

ABSTRACT: Exploring potential associations between small molecule drugs (SMs) and microRNAs (miRNAs) is significant for drug development and disease treatment. Since biological experiments are expensive and time-consuming, we propose a computational model based on accurate matrix completion for predicting potential SM-miRNA associations (AMCSMMA). Initially, a heterogeneous SM-miRNA network is constructed, and its adjacency matrix is taken as the target matrix. An optimization framework is then proposed to recover the target matrix with the missing values by minimizing its truncated nuclear norm, an accurate, robust, and efficient approximation to the rank function. Finally, we design an effective two-step iterative algorithm to solve the optimization problem and obtain the prediction scores. After

SUBMITTER: Wang S 

PROVIDER: S-EPMC10137058 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature