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If the percentage of a posteriori evidence is greater or equal than T1, then a regulatory phrase has been established.
The value acquired by the Boolean function for each configuration of the regulators is termed a regulatory phrase.
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From this information it is possible to generate regulatory phrases only for those genes with one regulator.
To infer the regulatory phrases from the microarray experiments analyzed in this work we used the value T1 = 75%.
We only used regulatory phrases for which the average of the a posteriori probability distribution was greater than 70% (activatory phrase) or smaller than 30% (inhibitory phrase).
We will refer to the regulatory phrases for which F = 1 as activatory, and those for which F = 0 as inhibitory.
Although random, these functions were constructed in accordance with the fraction of positive regulatory phrases inferred from real gene expression profiles.
Thus, in the absence of other knowledge, we used random regulatory phrases constructed with gene expression probabilities inferred from microarray experiments.
However, the overwhelming majority of regulatory phrases for the gene transcription networks of E. coli, S. cerevisiae and B. subtilis are still unknown.
Such models must take into account not only the evolution of the network topology, but also the emergence of the regulatory phrases through which the genes interact.
Figure 5 shows the inference success (the fraction of regulatory phrases form simple regulations that matched the phrases obtained from the curated databases) as a function of the threshold T0.
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