LRLSHMDA: Laplacian Regularized Least Squares for Human Microbe-Disease Association prediction.

ABSTRACT: An increasing number of evidences indicate microbes are implicated in human physiological mechanisms, including complicated disease pathology. Some microbes have been demonstrated to be associated with diverse important human diseases or disorders. Through investigating these disease-related microbes, we can obtain a better understanding of human disease mechanisms for advancing medical scientific progress in terms of disease diagnosis, treatment, prevention, prognosis and drug discovery. Based on the known microbe-disease association network, we developed a semi-supervised computational model of Laplacian Regularized Least Squares for Human Microbe-Disease Association (LRLSHMDA) by introducing Gaussian interaction profile kernel similarity calculation and Laplacian regularized least squar

SUBMITTER: Wang F 

PROVIDER: S-EPMC5548838 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature