I received my Ph.D. in ‘Computational Biology’ from Jamia Millia Islamia University, New Delhi (India). During my graduate research, I analyzed microarray data from tuberculosis patients, identified differentially expressed genes, and built gene interaction networks to reveal potential key regulatory genes that respond against the pathogen infection in the host. Further, I also worked in the field of “Network Medicine” which plays a crucial role at the cellular level since most cellular components are linked to each other via complex regulatory and metabolic mechanisms and protein-protein interactions. This study provided us with the opportunity to focus on the untouched aspects of any disease, in particular with their distant related gene-sets (meaning genes associated with other diseases), and to work in synergy to have a collective physiological effect on one’s pathological phenotype. Also, it supports the concept of applying network-based approaches to elucidate drug-target interactions and providing new research routes concerning a novel application of drugs not yet investigated in the specific context of TB and its associated noncommunicable diseases.
Currently, I am working as a research scholar (Bioinformatician) in the laboratory of Dr. Gabriela Chiosis at MSKCC. My research is aimed at analyzing epichaperomics datasets to derive relevant biological information. Epichaperomics is an emerging omics to study context-dependent protein-protein interaction (i.e. interactome) network perturbations in complex diseases. The disease interactome is a map of how individual stressors or a combination thereof alter interaction networks, including protein-protein interaction networks, and perturb the system as a whole. Epichaperomes (scaffolds composed of tightly bound chaperones, co-chaperones, and other factors) mediate how, under stressor conditions, thousands of proteins anomalously interact and organize inside cells, which aberrantly affects the function of protein networks, and in turn, cellular phenotypes. Therefore, capturing epichaperomes and the proteome at large negatively impacted by these critical scaffolds provides informative clues for direct access to interactome perturbations in diseases like cancers and other neurodegenerative diseases.