Biology Reference
In-Depth Information
Fig. 19.3
Ribonic spectra of the same sample as in Fig.
19.2
. Only those RNAs are selected whose
levels meet the quantitative requirement that NO
<
AF
<
BE, where NO - normal, AF
¼
tumors
after drug treatment, and BE
¼
tumors before drug treatment
tissues before (BE) drug therapy (see the third column in Table
19.2
). All other
cases, including the two cases shown in the fourth column of Table
19.2
, then
represent
negatively drug-responding RNAs.
From the s-ribons shown in Fig.
19.2
, it was relatively easy to select, out of the
54 energy-metabolizing RNAs, the 31 “positively drug-responding RNAs” whose
s-ribons are shown in Fig.
19.3
.
The ribonoscopic analysis of microarray data presented above has been based on
raw data without any clustering. But the same principle of
sandwiching
the AF
sample between the NO and BE samples (which may be referred to as the Principle
of “sandwiching AF between NO and BE,” or the “sandwiching AF between NO
and BE principle”) can be applied to microarray data after clustering with
ViDaExpert as schematically illustrated in Fig.
19.4
. Panel a shows a typical ribonic
(such as glycolytic, respiratory, or protein synthesis related) of a normal cell type.