A Computational Framework for Multilevel Morphologies

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Complex systems in general exhibit a hierarchical organisation that has a crucial role in
the static and dynamic characteristics of the systems themselves. These properties are highly
dependent by the principles of downward and upward causation, where the behavior of the
parts (down) is determined by the behavior of the whole (up), and the emergent behaviour
of the whole is determined by the behaviour of the part. An example is given by biological
systems: they are organised in different levels proteins, cells, tissues and so on and the
constant interplay among these levels gives rise to their observed behaviour and structure. In
this contest, an emblematic process is morphogenesis, which takes place at the beginning of
the animal life and is responsible for the formation of the animal structure. Morphogenesis
phenomena includes both cell-to-cell communication and intracellular dynamics: they work
together, and influence each other in the formation of complex and elaborate patterns that
are peculiar to the individual phenotype.
We took inspiration from these biological phenomena to realise a computational frame-
work to investigate both biological and artificial organisms capable to autonomously self-
organise in complex structures. The computational framework allows the reproduction of
multi-level and multi-compartments dynamics using the biochemical metaphor. It is based
on information a high-level language to specify system structure, inner chemical behaviours, and
stochastic actions to change system structure, and (ii) a simulation engine implementing an
optimised version of Gillespie's SSA (stochastic simulation algorithm), which allows to
exactly foresee the chemical evolution/diffusion of substances in the system.
On the one hand, the framework aims at being a tool to investigate the realisation of self-organising morphogenetic systems, i.e. artificial systems which self-organise themselves exploiting bio-inspired morphogenetic processes.
On the other hand this framework can be useful for modelling and simulation purposes of
biological organisms during morphogenesis. One key mechanism in this contest is the spatial
pattern formation of gene expressions. In particular we have
investigated some phenomena that are responsible for the generation of Drosophila embryo
segments, modelling the interaction among pathways inside the cell, that is responsible for its
stabilisation into a specific genetic expression, and the the cell-to cell interactions mediated
by cues, that enhance or inhibit the original cell?s activity and cause the formation of regions
of cells with similar activity.