Ilya Nemenman, Los Alamos National Laboratory

21 December, 2008

Sunday 11:30, Fishbach 430

 

Even the simplest biochemical kinetics networks often have more degrees of freedoms than one can (or should) analyze. Can we ever hope to do the physicists' favorite trick of coarse-graining, simplifying the networks to a much smaller set of effective dynamical variables that still capture the relevant aspects of the kinetics? I will argue first that the problem is more complicated than one might think, showing how naive, yet popular, approaches can lead to errors even in seemingly simple cases. I will argue then that methods of statistical field theory on the one hand and of machine learning on the other provide hints at the existence of rigorous coarse-grained methodology in biochemistry. However, we are still far away from solving the problem in its entirety.

 
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