Structure of Genetic Regulatory Networks: Evidence for Scale Free Networks
نویسنده
چکیده
The expression of some genes increases or decreases the expression of other genes forming a complex network of interactions. Typically, correlations between the expression of different genes under different conditions have been used to identify specific regulatory links between specific genes. Instead of that “bottom up” approach, here we try to identify the global types of networks present from the global statistical properties of the mRNA expression. We do this by comparing the statistics of mRNA computed from different network models, including random and fractal, scale free networks, to that found experimentally. The novel features of our approach are that: 1) we derive an explicit form of the connection matrix between genes to represent scale free models with arbitrary scaling exponents, 2) we extend Boolean networks to quantitative regulatory connections and quantitative mRNA expression concentrations, 3) we identify possible types of global genetic regulatory networks and their parameters from the experimental data.
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