Ribonoscopy and Personalized Medicine - Molecular Theory of the Living Cell - page 585

Chapter 18
Ribonoscopy and Personalized Medicine

As pointed out in Sect. 12.6 , microarrays can be used to measure either DNA or
RNA from cell samples (see Fig. 12.5 ) . Hence, it may be useful to coin two words,
ribonoscopy and deoxy-ribonoscopy to distinguish between these two types of
measurements. Conflating these two different measurements can lead to logical
errors in interpreting microarray data (Ji et al. 2009a). The term “ribonoscopy” is
composed of two stems - “ribo-” meaning ribonucleic acid or RNA , and “-scope”
meaning to look carefully or to see - and hence “ribonoscopy” literally means “to
carefully look at RNAs” (rather than genes or DNA) with respect to the changes in
both their sequences (or kinds, quality) and abundances (also called levels or
concentrations, quantity). More formally ribonoscopy can be defined as
The study of the genome-wide RNA sequences and concentrations inside the cell
measured with cDNA microarrays and visualized as spectra (called ribonic spectra) with
the y -axis registering RNA levels and the x -axis recording time, structure, or other related
variables. (18.1)

It is often useful to distinguish between the raw, unprocessed microarray data
and the results of the analysis of the raw data using software such as hierarchical
clustering (Eisen et al. 1998) and ViDaExpert (Gorban and Zinovyev 2004, 2005).
The former (i.e., RNA trajectories) is referred to as “ribons” (see Sects. 12.8.2 and
12.8.3 ) and the latter (i.e., 2- or 3-D displays of the results of analysing microarray
data) as “ribonic spectra” or “ribospectra.” The relation among ribons, computer-
assisted analytical tools, and ribonic spectra can be illustrated using an analogy
between optical spectra in physics and ribonic spectra as shown in Fig. 18.1 . Thus
ribons are akin to light, computer softwares are analogous to a prism, and ribonic
spectra are comparable to optical spectra.
The content of ribonoscopy is explained in a greater detail in Table 18.1 . There
are two major types of ribons - (1) the t-ribons , namely, time series as exemplified
by RNA trajectories (e.g., Fig. 9.1 ) and (2) what is here referred to as the s-ribons,
or structure series (see Table 9.1 and Figs. 19.2 and 19.3 ) in analogy to “time
series.” These two types of ribons are the inputs to ribonoscopy as indicated in the
first column of Table 18.1 . The raw data from microarray measurements on n RNAs