Honors & Awards
Young Investigator Award, BRCA Foundation (01/01/2018)
Doctor of Philosophy, Tata Institute of Fundamental Research (2016)
Bachelor of Science, University Of Delhi (2011)
Current Research and Scholarly Interests
My research at Stanford is focused on developing machine learning methods to analyze and integrate large genomic datasets. Currently, I am applying machine learning to the study of cancer evolution, particularly of BRCA+ breast cancers. In past research, I applied high-throughput functional genomics, deep learning and mathematical modeling to study the structure and function of bacterial genomes and identify potential drug targets in malarial parasites.
Regulation of Global Transcription in Escherichia coli by Rsd and 6S RNA
G3: GENES, GENOMES, GENETICS
View details for DOI 10.1534/g3.118.200265
Genome scale patterns of supercoiling in a bacterial chromosome
DNA in bacterial cells primarily exists in a negatively supercoiled state. The extent of supercoiling differs between regions of the chromosome, changes in response to external conditions and regulates gene expression. Here we report the use of trimethylpsoralen intercalation to map the extent of supercoiling across the Escherichia coli chromosome during exponential and stationary growth phases. We find that stationary phase E. coli cells display a gradient of negative supercoiling, with the terminus being more negatively supercoiled than the origin of replication, and that such a gradient is absent in exponentially growing cells. This stationary phase pattern is correlated with the binding of the nucleoid-associated protein HU, and we show that it is lost in an HU deletion strain. We suggest that HU establishes higher supercoiling near the terminus of the chromosome during stationary phase, whereas during exponential growth DNA gyrase and/or transcription equalizes supercoiling across the chromosome.
View details for DOI 10.1038/ncomms11055
View details for Web of Science ID 000373155100001
View details for PubMedID 27025941
View details for PubMedCentralID PMC4820846
- The Impact of Next-Generation Sequencing Technology on Bacterial Genomics A Systems Theoretic Approach to Systems and Synthetic Biology II: Analysis and Design of Cellular Systems 2014