Our group is developing a data hub for aging and microbiome research. This hub will bring together host-associated microbiome data from the public domain and will feature data integration strategies and data compilations. We will further use the integrated data compilations to gain new insights into the interactions between the microbiome and aging. The web server will be a valuable resource for researchers and a knowledge hub for the community.
Our research group is dedicated to exploring the dynamic interactions between the microbiome and the host during the aging process. To accomplish this, we are utilizing multi-omic datasets and a variety of approaches, including the study of community-level interaction models, examination of microbial evolution, and development of causal models. Our ultimate goal is to identify key trends and patterns that may be relevant to aging and to gain a deeper understanding of the underlying biology of these interactions. By advancing our understanding of the microbiome-host dynamic during aging, we hope to uncover new insights that may inform the development of therapies and interventions for age-related diseases.
Our research group is working to identify microbiome-based biomarkers and therapeutic targets for aging and age-related diseases. By constructing prediction models based on the microbiome, we aim to identify key indicators of health and disease that may be relevant to aging. We are particularly interested in promoting healthy aging and are studying not only healthy-aging cohorts and animal models but also large-scale age-related diseases to identify potential interventions and therapies. This research has the potential to provide important insights into the role of the microbiome in health and disease and to inform the development of effective interventions to promote healthy aging.