Therefore, we have to address some critical methodological issues, just to mention a few.- What kind of relationships exists among the lower levels (i.e., molecular) and the
highest ones (cell, tissues, organs)? This question can be more precisely reframed as
follows: how the intrinsic stochastic activity occurring at the genome level could
ultimately end up into a deterministic behavior, as such we observe at the cell or tissue
level [15]? Indeed, both stochastic gene expression and protein conformational noise
[16] contribute in generating phenotypic heterogeneity from which the most suit-
able configuration can be explored by the cell to “make” appropriate decisions
conferring it with remarkable phenotypic plasticity. There is no doubt that gene
expression and enzymatic pathways are finely tuned by gene regulatory networks
(GRN) according to nonequilibrium dynamics [17]. We can now appreciate and
understand more deeply such complex behavior than a few years ago. Yet, gene and
molecular activity regulation only partially rely on driving cues acting at the molecu-
lar, local level, while they are strongly modulated by cues and constraints dependent
on higher levels and tightly embedded within the specific biological field [18].
Compelling evidence claims that order in living systems is mostly imposed by high-
level, general constraints and forces (including electromagnetic, gravity, and cell-
tissue-dependent mechano-transduced forces) [19, 20]. Definitely, phenotypic
switching can result from stochastic (genetic and nongenetic) rather than by deter-
ministic events alone (genetic), while higher order constraints altogether with the
activation of specific regulatory network configuration will help in stabilizing the cell
fate commitment [21]. Systems Biology tries to identify these factors by investigating
the levels upon which these kinds of interactions are likely to happen, that is to say the
mesoscopic level, according to the definition provided by Laughlin [22]. The search
for parameters that can help in (quantitatively) describing biological process implies a
double effort: (a) identification of the minimum number of “observables” required
for a proper description of the system’s behavior, (b) assessment of the (quantitative)
relationships among variables in order to reconstruct a reliable mathematical model.
That approach will likely enable us to infer previsions from data as well as to detect
critical transition points. - Molecular biology, through a “classical” reductionist approach, taught us how some
selected and “compartmentalized” biochemical processes are mechanistically linked
to each other and how biochemical cascades operate within the cell. Yet, how the
“parts” are integrated is still an open question. Moreover, we still do not know how
those parts contribute in shaping the whole and, in turn, how the whole drives and
“canalizes” biochemical pathways. This observation has a huge body of consequences
and implies that we have to rethink not only the theoretical basis of biology but also
our experimental methodology. The natural world consists of hierarchical levels of
organization that range from subatomic particles to molecules, ecosystems, and
beyond. Each level is both characterized and governed by emergent laws that do
not appear at the lower levels of organization [23]. This implies that, in order to
explain the features and behavior of a whole system, we require atheorythat operates
at the corresponding hierarchical level. For instance, emergent phenomena that
occur at the level of the organism cannot be fully explained by theories that describe
events at the level of cells or macromolecules. As forecasted by Paul Weiss: “There is
no phenomenon in a living system that is not molecular, but there is none that is only
molecular, either. [The molecule-based approach] ignores the relevance of
vi Preface