AUTHOR=Qu Jia , Zhao Yan , Yin Jun 

TITLE=Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 10 - 2019

YEAR=2019

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2019.00291

DOI=10.3389/fmicb.2019.00291

ISSN=1664-302X

ABSTRACT=Studies have shown that microbes exist widely in human body and are closely related to human complex diseases. Predicting potential associations between microbes and diseases is conducive to understanding the mechanisms of complex diseases and can also facilitate the diagnosis and prevention of human diseases. In this paper, we put forward Matrix Decomposition and Label Propagation for Human Microbe-Disease Association prediction (MDLPHMDA) on the basis of the dataset of known microbe-disease associations collected from the database of HMDAD, Gaussian interaction profile kernel similarity for diseases and microbes, disease symptom similarity. Moreover, the performance of our model was evaluated by means of leave-one-out cross validation and 5-fold cross validation, and the corresponding AUCs of 0.9034 and 0.8954+/-0.0030 were gained, respectively. In case studies, 10, 9, 9 and 8 out of the top 10 predicted microbes for asthma, colorectal carcinoma, liver cirrhosis and type 1 diabetes were confirmed by literatures, respectively. Overall, evaluation results showed that MDLPHMDA has good performance in potential microbe-disease associations prediction.