Abstract
Plenty of microbes in our human body play a vital role in the process of cell physiology. In recent years, there is accumulating evidence indicating that microbes are closely related to many complex human diseases. In-depth investigation of disease-associated microbes can contribute to understanding the pathogenesis of diseases and thus provide novel strategies for the treatment, diagnosis, and prevention of diseases. To date, many computational models have been proposed for predicting microbe–disease associations using available similarity networks. However, these similarity networks are not effectively fused. In this study, we proposed a novel computational model based on multi-data integration and network consistency projection for Human Microbe–Disease Associations Prediction (HMDA-Pred), which fuses multiple similarity networks by a linear network fusion method. HMDA-Pred yielded AUC values of 0.9589 and 0.9361 ± 0.0037 in the experiments of leave-one-out cross validation (LOOCV) and 5-fold cross validation (5-fold CV), respectively. Furthermore, in case studies, 10, 8, and 10 out of the top 10 predicted microbes of asthma, colon cancer, and inflammatory bowel disease were confirmed by the literatures, respectively.
Highlights
As far as we know, microbes are ubiquitous in our living environment, and they occupy most habitats including humans and animals (Kouzuma et al, 2015)
For leave-one-out cross validation (LOOCV), one of the 450 confirmed microbe–disease associations pairs was used as a test sample while the left 449 associations were used as the training samples
For 5-fold CV, we randomly divided the 450 confirmed microbe–disease association pairs into five subsets, where one subset is used as test samples and the remaining four subsets as training samples
Summary
As far as we know, microbes are ubiquitous in our living environment, and they occupy most habitats including humans and animals (Kouzuma et al, 2015). The microbes are mainly classified into fungi, archaea, bacteria, protozoa, and viruses in the human body (Methé et al, 2012; Sommer and Bäckhed, 2013). More and more studies have shown that most of these microbes are friendly to human beings and play a significant role in the physiology processes of the human body, such as regulating gastrointestinal development, providing protection for pathogens, and enhancing metabolic capability (Ventura et al, 2009). Abnormal changes in the microbe communities may affect human health and diseases. Low microbial diversity could result in inflammatory bowel disease and obesity (Turnbaugh et al, 2009; Qin et al, 2010).
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