
Systems Genomics Modeling of Multi-drug Resistance in Mycobacterium tuberculosis
The project involves (i) detecting all mutations in a large cohort of WGS (Whole Genome Sequence) data of Mycobacterium tuberculosis (Mtb), (ii) investigating if those mutations interact with each other to express drug-resistance trait, and (iii) develop machine learning powered tools to automate data processing pipeline and effectively predict drug-resistance in WGS from Mtb.
Research Themes:
Computational Genomics Lab (CGL), Transforming Global health with AI (TOGAI)
Project Category:
Bioinformatics