Human Microbe-Disease Association Prediction Based on Adaptive Boosting.

ABSTRACT: There are countless microbes in the human body, and they play various roles in the physiological process. There is growing evidence that microbes are closely associated with human diseases. Researching disease-related microbes helps us understand the mechanisms of diseases and provides new strategies for diseases diagnosis and treatment. Many computational models have been proposed to predict disease-related microbes, in this paper, we developed a model of Adaptive Boosting for Human Microbe-Disease Association prediction (ABHMDA) to reveal the associations between diseases and microbes by calculating the relation probability of disease-microbe pair using a strong classifier. Our model could be applied to new diseases without any known related microbes. In order to assess the prediction po

SUBMITTER: Peng LH 

PROVIDER: S-EPMC6189371 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature