FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association.

ABSTRACT:

Background

In the process of post-transcription, microRNAs (miRNAs) are closely related to various complex human diseases. Traditional verification methods for miRNA-disease associations take a lot of time and expense, so it is especially important to design computational methods for detecting potential associations. Considering the restrictions of previous computational methods for predicting potential miRNAs-disease associations, we develop the model of FKL-Spa-LapRLS (Fast Kernel Learning Sparse kernel Laplacian Regularized Least Squares) to break through the limitations.

Result

First, we extract three miRNA similarity kernels and three disease similarity kernels. Then, we combine these kernels into a single kernel through the Fast Kernel Learning (FKL) model, and use spa

SUBMITTER: Jiang L 

PROVIDER: S-EPMC6311941 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature