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Metagenomic approaches enable unbiased whole microbial community characterizations but cannot differentiate between living and dead microbes, which is however crucial for virulent pathogen detection. Traditional methods for identifying living microbes are labor-intensive and time-consuming.
This project aims to develop a computer-based framework using nanopore sequencing to predict microorganism viability from raw metagenomic squiggle data.
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