We expect that Genetic Self-assembly will be useful in nanotechnological and biotechnological construction of complex systems. The work points to the general utility of encoding self-assembling building blocks in biological evolution, for general problem solution.
The self assembly algorithm we employed was deterministic and established the feasibility of inductive generalization with genetic self assembly. We have extended this work to more realistic models of self assembly, especially including erroneous assembly in a physical environment with thermodynamic fluctuations. This shows that the results are not dependent upon a precise deterministic self-assembly algorithm: the system develops robust solutions.
Further extensions, to structures in three dimensions and
more freedom in geometrical shape space are possible.
Genetic self-assembly has been connected with the evolving amphiphilic systems modelling framework.
It has also given rise to algorithmic self-assembly, in which modular algorithmic control structures self-assembly to evolving programs.