1 Introduction
High-throughput genomic, transcriptomic, proteomic and metabolomic (“omics”)
analyses have enabled the further development of biological sciences to an unprece-
dented level. Accordingly, the contemporary medical research is also taking full
advantage of these technologies, and it is on the way to discover their powerful
potential. Integration of all omics data is the only way for decoding the basic rules
that control the function of cells, tissues, organs, and whole organisms. Addition-
ally, an extensive bioinformatic support is absolutely necessary to integrate all
omics data sets in order to decode the underlying principle that controls the
complex functions of a living system like human organism. Bioinformatic work
requests an extensive computational support, and statistical modeling is needed to
connect all omics data sets. It speeds up the generation of working hypothesis and
yields in a deep insight in physiology and disease generation. This systematic
approach will lead to theranostic (therapeutic and diagnostic) strategies with
novel biomarkers that are discovered by use of one of more high-throughput
omics technologies and will pave the way to personalized medicine as the
final goal.
According to Pesce et al.,^1 “the -omic cascade, from the potentiality of‘what can
happen’(genome) through‘what appears to happen’(transcriptome) and‘what
makes it happen’(proteome) to‘what has happened’(metabolome) embodies the
paradigm of‘what needs to be modeled’by use of bioinformatic tools.” This
cascade is presented in Fig. 1. The role of each omics technology in personalized
medicine is precisely defined in the sentence that is cited above, and their appli-
cation was also recently discussed.^2 The genomic technology yields in determination
of genetic profile of a patient that is associated with increased risks of developing
specific disease. Further molecular characterization and profiles acquired by
transcriptomic and proteomic technologies represent the host’s individual and
specific nature and in the case of a disease patient’s encountered pathologic lesion.
And finally, determination of small molecules by metabolomic technology enables
to see the result of the pathologic process, e.g., in patients body fluids, usually blood
plasma and serum and/or urine. However, the further we are in the cascade shown in
Fig. 1 , the complicated gets the picture. As defined above, the genetic profile
determines patient’s risk to develop a specific disease (e.g., diabetes, cancer, or
cardiovascular diseases). The identification of the presence of such condition can
provide important information for treating clinician and lead to targeted and early
treatment, but the presence of specific disease has to be confirmed by other
methods.
By definition, transcriptomics is the expression profile of RNAs in a specific cell
or specific tissue, in a particular moment or condition. This profile captures its
(^1) Pesce et al. ( 2013 ), pp. 24–28.
(^2) Pavelic et al. ( 2015 ).
180 D. Josic ́and U. Andjelkovic ́