Computational approach to modeling microbiome landscapes associated with chronic human disease progression.

ABSTRACT: A microbial community is a dynamic system undergoing constant change in response to internal and external stimuli. These changes can have significant implications for human health. However, due to the difficulty in obtaining longitudinal samples, the study of the dynamic relationship between the microbiome and human health remains a challenge. Here, we introduce a novel computational strategy that uses massive cross-sectional sample data to model microbiome landscapes associated with chronic disease development. The strategy is based on the rationale that each static sample provides a snapshot of the disease process, and if the number of samples is sufficiently large, the footprints of individual samples populate progression trajectories, which enables us to recover disease progression pat

SUBMITTER: Li L 

PROVIDER: S-EPMC9380910 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature