Dr. Andricioaei earned his Ph.D. at Boston University and a Postdoctoral Fellowship at Harvard University. His research focus is theoretical and computational molecular biology." He describes it below: "Our research explores theoretical and computational topics at the interface between structural molecular biology and physical chemistry. It hinges on the central theme of developing and applying computer and modeling methods to describe, in terms of dynamics and thermodynamics, biologically important molecular processes, with the aim to complement, enhance or predict experimental findings. Research directions include:

Computer Simulations of DNA-Binding Machines. Protein-DNA interactions are essential in such crucial cellular functions as replication, repair, transcription or recombination. Many enzymes at and ahead of the replication fork affect large DNA fragments. For instance, topoisomerases undo DNA knotting. Others, like helicases and polymerases, are biomolecular motors; they use the energy of binding and/or hydrolysis of nucleotides to do mechanical work on the DNA fragments to which they bind. We have an avid interest in the theoretical description of these fundamental genetic processes through massively parallel computer simulations.

Dynamics–Function Relationships. Connections to NMR Relaxation. An accurate measure of free energy, important for protein/RNA stability or ligand binding, has to include the entropy manifested in molecular flexibility. On the experimental side, this dynamic aspect is brought in by developments in solution NMR spectroscopy, which measures motion by relaxation experiments. Molecular dynamics simulation is an important tool to complement these measurements and to connect dynamics to entropy.

Enhanced Sampling in Path Space. Many important equilibrium and kinetic properties of chemical systems (including proteins and nucleic acids) can be cast in terms of paths in multi–dimensional spaces. Sampling and optimization algorithms we have developed for the conformational space can be generalized and adapted to the space of paths. We see fertile ground for theoretical and computational work on several categories of paths, from chemical-reaction paths to paths in the sequence space of evolving proteins.