phenomena and to identify biochemical events, including cell sig-
naling, cell cycle, and different biological pathways [1, 2].
In agreement with this perspective, new opportunities are dis-
closed to understand biological systems and functions of cellular
tissues and components, leading to interesting predictions of
biological interest, even for an evidence-based, personalized
approach to treatment [3]. Nowadays, system biology is becoming
the borderline of modern biological research with a great amount
of data stemming from the new omics approaches. This complex
situation can be very challenging to be understood without a
network or a systems point of view, with the associated computa-
tional analyses [3, 4].
Furthermore, a systems biology perspective will contribute to
reshaping our view regarding the theory of biological phenomena
[4]. To understand the system biology approach in modern
biological research we need the powerful computational tools cur-
rently available, which are used to manage the large-scale data sets
of information on cellular structures, genetics, proteins, cytoskele-
ton [5]. These types of tools are able to build the dynamic system
models to perform the simulation and interpretation of the
mechanisms of some cellular behavior from a system viewpoint
[6, 7]. There are several mathematical techniques that were created
on the basis of systems biology and have been developed to study
the methodological properties of the complex living networks
[8]. At present, mathematical modeling is gaining increasing
importance to explain and predict the behavior of biological
systems.
New system biology applications are continuously appearing,
spurred by the development of tools and techniques [9–11]. Such
instruments leverage on the platforms for the local and global
analysis, e.g., high-throughput genomics and proteomics equip-
ment. The important point here is to define the quantitative models
that are able to decipher the biological information [12].
We believe that quantitative models of System biology are help-
ful in identifying key dynamical features, which would have a fruitful
impact on pharmaceutical and medicinal practice. According to Hir-
oaki Kitano the technical and system level analysis not only permits
the visualization for molecular interactions but also speeds up the
measurement with various developed methodologies [13].
The borders of System biology are not yet clearly defined. From
the basic biological knowledge, System biology can be brought to
consider also predictive capabilities for patients, in case of a possible
healthcare service supply. Therefore, this field of investigation can
have far-reaching consequences, in the patients’ standpoint.
Moreover, the wealth of data available about a particular
biological process is usually not cast in a harmonized form, since
many different sources can be used, typically. Indeed, data
structured by the System biology approach are heterogeneous:338 Garima Verma et al.