Cell Language Theory, The: Connecting Mind And Matter

Applications of the Cell Language Theory to Biomedical Sciences 315

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

7.3.2 PDE-Based Method for Identifying Patient-Specific

Breast Cancer Genes

The PDE was derived from the Planck radiation equation (PRE) in 2008

[25, pp. 343–68] by replacing the universal constants and temperature

with free parameters, A, B, and C (see Eqs. (8.1) and (8.3) in Figure 8.1).

The unusual feature of PDE is that it fits almost all long-tailed histograms

generated in physics, biology, neuroscience, economics, and linguistics

(see Chapter 8), just as the Gaussian distribution equation fits normally

distributed histograms [330].

The procedure or the algorithm for applying PDE to analyzing human

breast cancer data consists of four main steps as summarized in Figure 7.15:

(1) Transform selected portions of the genome-wide mRNA data into

histograms using the histogram software available in Excel. The

selection criteria can be (i) random (Figure 7.18), (ii) based on the

mechanism phenotypes defined in Figure 7.11 (Figure 7.19), or (iii)

based on metabolic pathways (Figures 7.16 and 7.21).

Figure 7.15 The procedure (or algorithm) for analyzing DNA microarray data using

PDE. áSMñ = the average survival months of breast cancer patients after drug treatment.

Microarray Data

Histograms

PDE

A, B, C parameter values

A vs C plots

y= ax + b

Drug-induced ∆slope vs <SM> plot

1

2

3

4

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