Associate Professor

• Sep 2019 - Present

Senior Assistant Professor

• Jul 2012 - Sep 2019

Research Assistant

• Jan 2012 - Jul 2012

Graduate Student

• Jan 2006 - Dec 2011

Redesigning the specificity of a protein towards a DNA sequence finds immense potential for nucleic-acid based therapeutic approaches. However, rational redesigning of protein-DNA surfaces suffers from our limited understanding of protein-DNA recognition mechanisms. Specifically, knowledge of mechanisms by which proteins bind to noncognate sequences is essential to develop a comprehensive picture of protein-DNA recognition. My thesis focussed on investigating the interactions of proteins with their noncognate DNA sequences. EcoRI, an otherwise well-studied restriction enzyme, was chosen as the model system. Results revealed previously unknown information such as (i) protein-induced sequence-dependent DNA conformation, sequence-dependent changes in the (ii) intrinsic dynamics of the protein and (iii) dynamics of intercalating waters.

Junior Research Fellow

• Aug 2005 - Dec 2005

With nuclear hormone receptors being potential drug targets, I was involved in characterizing the reportoire of nuclear hormone receptors in the model vertebrate genome, Tetraodon nigroviridis (Teloest fish), by comparative functional genomics. With nuclear hormone receptors being potential drug targets, I was involved in characterizing the reportoire of nuclear hormone receptors in the model vertebrate genome, Tetraodon nigroviridis (Teloest fish), by comparative functional genomics.

Project Assistant

• Dec 2004 - Jun 2005

With vast amount of DNA sequence data being generated using several advanced technologies, it has become essential to use sophisticated techniques to robustly identify coding regions in the DNA sequences. I was involved in developing a method based on multifractal formalism and Support Vector Machine to capture the local patterns in the DNA sequence and distinguish coding regions from non-coding regions. With vast amount of DNA sequence data being generated using several advanced technologies, it has become essential to use sophisticated techniques to robustly identify coding regions in the DNA sequences. I was involved in developing a method based on multifractal formalism and Support Vector Machine to capture the local patterns in the DNA sequence and distinguish coding regions from non-coding regions.