After completing my Bachelors and Masters in Bioinformatics, I shifted my focus towards Computational Drug Discovery and received a PhD from the University of Helsinki, Finland in 2016. My doctoral thesis work mainly focused on developing field-based proteochemometric approaches that could support visualization of affinity and selectivity related features of kinases and serine proteases.
In 2017, I started as a post-doc in Saez-Rodriguez group to work on the PrECISE EU project that aims to develop both computational and experimental strategies ideal for the treatment of prostate cancer.
With the vast amount of omics, bioactivity and chemical structures data available in public databases, utilizing this data to build computational models that reflect the various biological phenomena could provide valuable input to address the unmet medical needs. My current research focuses on modeling the prostate cancer data to be able to predict the drug response profiles based on an individual’s genetic makeup.
My key areas of interest include Big data, Chemoinformatics, Personalized medicine and Predictive polypharmacology.
|2017-Present||Postdoctoral researcher, JRC-COMBINE, Saez-Rodriguez group (PrECISE project)|
|2012-2016||PhD in Computational Drug Discovery, University of Helsinki, Finland|
|2010-2012||Masters in Bioinformatics, University of Helsinki, Finland|
|2004-2008||Bachelor of Technology in Bioinformatics, SASTRA University, India|