Cell Language Theory, The: Connecting Mind And Matter

316 The Cell Language Theory: Connecting Mind and Matter

b2861 The Cell Language Theory: Connecting Mind and Matter “6x9”

(2) Using the Solver software available in Excel, determine the numeri-

cal values of A, B, and C of PDE, Eq. (8.3) (Figure 7.16).

(3) Plot A vs. C and determine the linear equation, y = ax + b, and the

associated correlation coefficient R^2 values (e.g., Figure 7.18). If the R^2

< 0.60, terminate the analysis and otherwise continue to the next step.

(4) Plot the average survival month, SM, of each group vs. the drug-

induced change in the slope of the A vs. C plots in (3) (Figures 7.18,

bottom panel, and 7.20).

As shown in Figure 8.3(e), the genome-wide RNA levels measured in

human breast tissues from 20 patients fitted PDE almost perfectly. Rather

than making one histogram out of the genome-wide RNA levels, we inves-

tigated the RNA levels of a few metabolic pathways shown in Table 7.4.

Some examples of the fitting of these pathways to PDE are displayed in

Figure 7.16. Compared to the histogram of the whole genome (with ~ 5000

genes or ORFs), those of the 3 metabolic pathways (each containing

Figure 7.16 The fittings of PDE to the mRNA levels of the human breast cancer tissues.

The x-axis represents the RNA level bin numbers and the y-axis represents frequency. CGI

= kinase binding protein; MAPK = mitogen-activated protein kinases; ZFP = zinc finger

proteins; WG = whole genomes of 20 patients (92,813 mRNA levels). The typical PDE

parameter values are given in Table 7.5.

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