In Prof. Charles Carter's lab, I worked with Dr. Jeff Roach to design a technique for protein structure comparison using Delaunay Tesselation, reducing the complexity of protein structure for high-throughput structural comparison (cf. Publications).
In Prof. Brian Kuhlman's lab, I conducted experiments, performing site-directed mutagenesis and Bodipy-labeled binding assays on the E2-E3 enzymes of the Ubiquitination Pathway. The main goal of this research was to study the presence of complimentary binding among a pair of Ubch70 (E2) and E6APi-HECT (E3) mutants rationally designed for studying the mechanisms underlying the Ubiquitination pathway.
In Prof. Ramanathan Sowdhamini's lab at the National Center for Biological Sciences, I worked on two projects: (i) Developing LemonGrass, a C++ library for performing structural bioinformatics analysis. The goal of this work was to engineer a generic and extensible object oriented class library in C++ which would assist structural biologists in performing computational analyses of proteins, DNA and RNA by parsing Protein DataBank (PDB) entries. A major objective of this project was using of efficient data structures for handling large PDB databases and ensuring extensibility by employing the C++ Standard Template Library.
In Prof. Somenath Biswas's group at the Indian Institute of Technology, Kanpur, I developed a rapid protein structure comparison tool, as a part of my undergraduate thesis.
In the laboratory of Dr. Narendra Karmarkar, I did research on improving the efficiency of the Karmarkar's algorithm for the 3-SAT problem. Karmarkar's Algorithm is well-known for solving linear programming problems. My project involved two parts: (i) introducing derived equality relations in the algorithm and reducing the duality gap. This also involved use of Tensor Optimization and Karmarkar's Interior Point Algorithm; and (ii) analysis of zeroes of large symmetric Gaussian matrices leading to verification of the Semicircular Law.
My long-term research objective is to apply physically-accurate, yet multidisciplinary computational approaches to generate experimentally-testable hypotheses for solving research problems in biology.