Design of Biomarkers

The assessment of microbial community health in diverse hosts, including humans, plants, and the environment, is a complex and debated topic. Imbalances in microbial communities can stem from various factors, necessitating the consolidation of extensive and intricate changes into a unified indicator. This project aims to discern biomarkers within microbial communities and propose an innovative model that leverages robust statistical analysis, as well as machine learning and deep learning techniques.

Given the requirement for a substantial volume of data to ensure dependable statistical analysis, machine learning, and deep learning methodologies, this project adopts a large-scale, data-driven approaches to compile high-quality datasets. Stringent quality control measures are implemented to scrutinize data obtained from diverse sources, which are then utilized to establish an index for evaluating the health of microbial communities.