Starts 25 Oct 2011 15:00
Ends 25 Oct 2011 20:00
Central European Time
ICTP
Leonardo da Vinci Building Luigi Stasi Seminar Room
Strada Costiera, 11 I - 34151 Trieste (Italy)
With the advancement of recording technology in various parts of biology, we can now observe many elements in a biological system at the same time. For instance we can measure the expression level of many genes using gene microarrays or spike trains from many neurons using multi-electrode arrays. Given this, an important and interesting question to ask is "can we use such data to infer interactions between elements of the system?". In this talk, I will describe toy versions of this problem. I will briefly describe how it can be done for an equilibrium Ising model, that is the inverse Ising problem; then I discuss inferring the interactions of a non-equilibrium Sherrington-Kirkpatrick model showing how Dynamical Mean-Field theory (naive mean field, TAP and exact MF) can be developed and exploited for inferring network connectivity.
  • M. Poropat