Archive for the ‘physics’ Category

“DNA in a tigh squeeze”

October 16, 2007

Today Rob Phillips ( gave a talk titled, “DNA in a tight squeeze: the other life of a macromolecular assembly.”

Phillips et al. study the atomic-level physics of DNA.  Their recent work focuses on DNA loops which are formed when transcription factors bind to regulatory sites.  Specifically, they modified the lac operon such that they can insert sequences of arbitrary length and content between the Oid and O1 sites.   A surprising result is that DNA is happiest to make loops of 75.5 base pair lengths, whereas the persistence length for DNA is 115 base pairs.  I think this result has ramifications for our understanding of the fitness of regulatory regions. I would like to see an experiment which explores evolutionary fitness with regard to loop length between cis-regulatory sites.

Phillips also showed results from his study correlating the osmotic pressure inside a viral capsid to the speed of genetic ejection.  His results show that viruses eject genetic material (into their host cell) very quickly at first.  However, as the inter-viral osmotic pressure declines, the rate of ejection also drops.  Eventually, the pressure reaches a point where no genetic material is ejected at all.  I have several questions about the content of the genetic material which may or may not be ejected.  Does it transcribe into a functional protein?  Or, does this “tail” material contain garbage which can safely be left inside the virus?

I find this research exciting because it intersects physics, chemistry, biology, statistics, and computer science.

(Finally: check-out the VIPER project for atomic-level exploration of viral structures) 


Forces of attraction

May 10, 2007

Peter Boothe and I are building a software tool for visualizing the Gnutella peer-to-peer network topology. Our dataset is huge, and comes from Dan Stutzbach’s PhD work. (Click here for publications by Dan).

Anyway, Peter and I designed a physics model to automatically layout the graph. Each node is a magnet, which repels other nodes. Each edge is a spring, which attracts conjoined nodes. I tip my hat to Peter for implementing an efficient quad-tree and N-body engine. Unfortunately, the Gnutella data contains 150,000+ nodes per snapshot. (That’s a really big graph!) Even on a quad-core PC with 4 GB RAM, our physics engine runs like a snail.

So, today I parallelized the code. . . but the improvement was only about 15%.

The bad news is that our software needs a lot of work before we can effectively visualize Gnutella data. However, the good news is that our software works really well for small graphs (like Internet AS data). We might not be accomplishing science, but at least we have a cool toy!