A sequence-matching model of complex interactions
We have recently proposed a network model based on information sharing, realized as a sequence matching condition between strings associated with nodes. We have applied this to modeling the transcriptional gene regulatory network of yeast, with very convincing results. A dilute Potts neural network model motivated by this approach can be solved by standard methods.
Istanbul Technical University and Feza Gursey Insitute

