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However, in computing M x) for the large networks of E. coli, S. cerevisiae and B. subtilis, we face the problem that the overwhelming majority of the regulatory functions (also termed regulatory phrases) that determine the combined effect of the regulators on their target genes are unknown.
The term (x t) - z) C represents the effect of the regulators on the genes; this term needs to be amplified for the use of DBI, because of the required discretization.
This function is plotted in Figure 3 figure supplement 1, together with the values of S* as a function of Y and R. Note that (1 − R) Y is the part of the expression mismatch that is not accounted for by the condition-response effect of the regulators.
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Finally, the numerical simulations are provided to illustrate the effect of the regulator.
Dr. Ruvkun's team reports in Nature a novel effect of the regulator: It can switch on in the worm's ordinary body cells, or somatic cells, two genes that are usually active only in the germline cells and are kept permanently switched off in the somatic cells.
For each upstream regulator that met these cutoffs, an activation Z-score, calculated by IPA, was determined by comparing the known effect of the regulator on each target gene (activation or suppression) to the observed changes in gene expression.
However, for a graphical visualization, a quantity given in an approximate magnitude is adequate, unless the sign of the RS value corresponds to the underlying effect of the regulator (i.e. + activator or - inhibitor).
In this regime the noise-propagation is very small and the condition-response effect of the regulator is high, that is, as expected, the most optimal solution is a very accurate regulation in which all benefits of the regulation stem from the condition-response effect.
Intuitively, these functions take into account the existence of dominant regulators such that, when present, override the effect of the other regulators.
The bias-corrected z-score is computed based on the proportion of target genes present in the dataset which are directionally regulated as expected according to known effects of the regulator on the target compiled from the literature.
Another effect of the regulated price for gas, which regulators acknowledge is deliberately set to ensure that customers pay less than the market rate, is that it artificially suppresses the price of gas, PSE&G contends.
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