To investigate how non-synonymous SNPs within protein-coding genes influence cancer cell susceptibility and progression. Cancer Research Case Study: Breast, Colon, Lung, Liver etc.
To systematically monitor antimicrobial resistance mechanisms worldwide, aiming to improve our comprehension of resistance dynamics and guide the development of focused intervention
To employ genomics approaches for the study of foodborne diseases by gaining insight into genetic factors underlying pathogen virulence, transmission dynamics, and antimicrobial resistance
To utilize genomics to study plant-pathogen interactions, with a focus on elucidating the genetic mechanisms governing pathogen virulence, host susceptibility, and disease resistance.
To employ environmental metagenomics across diverse sample types for public health purposes, to comprehensively assess microbial communities to monitor environmental health.
To leverage metagenomics techniques to provide insights into the underlying mechanisms linking the microbiome and diabetes, ultimately aiming to develop targeted interventions for improved management and prevention of the disease.
To discover and leverage biosynthetic genes from medicinal sources, integrating them into the development of peptide-based anti-cancer therapeutics using a multi-omics and machine learning approach
To pioneer a novel approach by integrating multi-omics data and cutting-edge machine learning techniques to systematically discover, optimize, and develop novel therapeutic antibacterial peptides sourced from diverse natural origins.
To systematically investigate and optimize peptides derived from microbial and plant sources for the development of targeted and effective anti-malarial drugs, addressing the urgent need for novel strategies against malaria and drug-resistant strains.
