Gene Network Models

Several models has been proposed in the literature to capture the notion of gene networks and allow mathematical solutions of the above computational problem.

• Linear Model
  This model, proposed by D'haeseleer et. al. [3], [2], assumes that expression level of a node in a network depends on linear combination of the expression levels of its neighbors
• Boolean Model
  Due to Liang, Fuhrman and Somogoyi [7]. It assumes only two distinct levels of expression - 0 and 1. According to this model a value of a node at the next step is boolean function of the values of its neighbors.
• Bayesian Model
  Due to Friedman et al. [6]. It attempts to give a more accurate model of network behavior, based on Bayesian probabilities for expression levels

In the rest of this document we shall concentrate only on the Boolean model. The reader is referred to the mentioned papers for more information regarding the other models.