Sentence examples for inferred phrases from inspiring English sources

In order to have a good statistics (more than 250 inferred phrases) and a high inference success (around 90%), in this work we have chosen T0 = 1.5 in E. coli and T0 = 1.3 in B. subtilis.

The inference success was established as the percentage of coincidences between our inferred phrases and the reported ones.

However, the total number of inferred phrases decreases with the threshold.

In the same graphs we have plotted the total number of inferred phrases (including the phrases from simple regulations).

Once a set of phrases has been successfully established, we determine the probability of gene expression as the quotient of activatory phrases between the total of inferred phrases.

To validate our methodology we compared only the inferred phrases for simple regulations with the ones reported in the RegulonDB or the DBTBS.

To validate our methodology for inferring regulatory phrases we use the nature of the regulation already reported in the data bases for the case of simple regulations, namely, when only one regulator determines the expression of the regulated gene (gene A is only regulated by gene B).

Although random, these functions were constructed in accordance with the fraction of positive regulatory phrases inferred from real gene expression profiles.

Using 223 microarrays to sample the gene expression space in S. cerevisiae [49], 152 microarrays for E. coli [49] [51], and 69 microarrays for B. subtillis [52], we inferred several regulatory phrases for each of these organisms.

Thatcher famously dismissed the very idea of society as a nanny-state fantasy — "there is no such thing" — and no offer of a hug could be inferred from her signature phrase, uttered during an early wave of popular discontent with her policies: "The lady's not for turning".

To infer the regulatory phrases from the microarray experiments analyzed in this work we used the value T1 = 75%.