My research concerns flexibility of proteins, in which there is some interest. The partition function is computed via a microscopic model with long range interactions arising from network ridgidity. Among other things, this technique can understand hot and cold denaturation of proteins, critical exponents for the alpha helix-coil transition, and flexibility (which correlates to activity). By identifying rigid and flexible regions in proteins, many insights into the protiens follow such as: how does the protein move, and thus what does is it's function within the cell? what parts of the protein are possible active sites, and thus can be targets for new drugs? Computing power consists of a cluster of four Intel based machines, with more serious hardware to come later. This technique falls in complexity between full-blown all-atom molecular dynamics simulations and simplistic "Go-like" beads on a string models of proteins. It is a valuable "arrow in the quiver" of possible techniques to address these very important questions. Monte Carlo techniques began by scientists literally rolling dice to guide the simulation - yet it is still in use today with computers rolling millions of dice per second.

A link to our first joint paper can be found here.

Our second paper on polypeptides and hot and cold denaturation can be found here.

Our third joint paper on proteins can be found here.

Our fourth paper, on the HP model of polypeptides can be found here.

My earlier research was extracting a correlation length from spin glass experiments. Our first publication on that issue can be found here.

Physics to Biophysics Transition

I found a nice article on biophysics which describes how even a great success such as the authors had comes in the face of great scepticism. Here is the link.

Here is an article from TIP (The Industrial Physicist) about the transition from physics to biology. It covers the transitions of a few people and shows that there are various paths which lead to the same goal.