Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion

Jitong Feng, Shengbo Wu, Hongpeng Yang, Chengwei Ai, Jianjun Qiao, Junhai Xu, Fei Guo

Abstract: Metabolomics has developed rapidly in recent years, and metabolism-related databases are also gradually constructed. Nowadays, more and more studies are being carried out on diverse microbes, metabolites and diseases. However, the logics of various associations among microbes, metabolites and diseases are limited understanding in the biomedicine of gut microbial system. The collection and analysis of relevant microbial bioinformation play an important role in the revelation of microbe–metabolite–disease associations. Therefore, the dataset that integrates multiple relationships and the method based on complex heterogeneous graphs need to be developed.