High throughput data generation helps in unraveling many underlying processes happening within cell at scale and precision hitherto unprecedented. As a result, vast amount of data has accumulated but their use is limited by the available algorithms and the questions being asked on them. My endeavor is to use in silico methods and computational tools to extract patterns in high throughput big data to answer relevant biological questions. 

Currently I am working with Dr Ranjan Perera at Johns Hopkins All Childrens Hospital, St Pete, FL. My research is focused on understanding Medulloblastoma subgroups specificity in light of epitranscriptomic modifications.

Previously, I have worked with Dr Dan Ohtan Wang to research epitranscriptomic dynamics in brain and its relevance in memory and learning. We are particularly interested in spatiotemporal dynamics of RNA methylation, the most prevalent RNA modification and its consequences on gene translation and protein regulation in brain and neuron plasticity.

During graduate study in the laboratory of Dr Vinod Scaria, as a DBT-BINC fellow, my primary goal was to make sense of the vast amount of data available and solve relevant biological problems by asking right questions. I analysed RNA-seq data of host cells infected with virulent Mycobacterium tuberculosis strains. I discovered, using computational techniques such as co-expression network analysis, guilt-by-association and computational framework, the potential functional role of long noncoding RNAs in co-regulation of important immune functions along with known transcription factors. I also analyzed publicly available whole genome sequences of M. tuberculosis to create a compendium of genetic mutations called ‘tbvar’ with a tool for clinical application during my graduate study. In future, I wish to take up a career in academia as well as continue my research, which will be benificial to the community.