Metagenome and machine learning approaches to exploit population health data of wastewater
In this project, we will explore total metagenome from wastewater, which are a trusted source of community-level population health data. We evaluate the correlation between the health records in a given locality and the corresponding wastewater metagenomic signatures.
The project aims to identify disease risk indicators using bioinformatics and data science, including machine learning. Furthermore, the research produces a cost-effective community-level alternative to generating health information for infection epidemiology and population health research.
Partners and funding