This project aims at understanding how cell fate decision emerges from
the overall intracellular network connectivity and dynamics. To achieve this goal
both small paradigmatic signalling-gene regulatory networks and their
generalization to highdimensional space were tested. Particularly, we drew
special attention to the importance of the effects of time varying parameters in
the decision genetic switch with external stimulation. The most striking feature of
our findings is the clear and crucial impact of the rate with which the time-dependent
parameters are changed. In the presence of small asymmetries and
fluctuations, slow passage through the critical region increases substantially
specific attractor selection by external transient perturbations. This has strong
implications for the cell fate decision problem since cell phenotype in stem cell
differentiation, cell cycle progression, or apoptosis studies, has been successfully
identified as attractors of a whole network expression process induced by
signalling events. Moreover, asymmetry and noise naturally exist in any
integrative intracellular decision network. To further clarify the importance of the
rate of parameter sweeping, we also studied models from non-equilibrium
systems theory. These are traditional in the study of phase transitions in
statistical physics and stood as a fundamental tool to extrapolate key results to
intracellular network dynamics. Specifically, we analysed the effects of a time-dependent
asymmetry in the canonical supercritical pitchfork bifurcation model,
both by numerical simulations and analytical solutions. We complemented the
discussion of cell fate decision with a study of the effects of non-specific targets
of drugs on the Epidermal Growth Factor Receptor pathway. Pathway output has
long been correlated with qualitative cell phenotype. Cancer network
multitargeting therapies were assessed in the context of whole network attractor
phenotypes and the importance of parameter sweeping speed
