Human Microbe-Disease Association Prediction With Graph Regularized Non-Negative Matrix Factorization.

ABSTRACT: A microbe is a microscopic organism which may exists in its single-celled form or in a colony of cells. In recent years, accumulating researchers have been engaged in the field of uncovering microbe-disease associations since microbes are found to be closely related to the prevention, diagnosis, and treatment of many complex human diseases. As an effective supplement to the traditional experiment, more and more computational models based on various algorithms have been proposed for microbe-disease association prediction to improve efficiency and cost savings. In this work, we developed a novel predictive model of Graph Regularized Non-negative Matrix Factorization for Human Microbe-Disease Association prediction (GRNMFHMDA). Initially, microbe similarity and disease similarity were constru

SUBMITTER: He BS 

PROVIDER: S-EPMC6223245 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature