This talk starts with a brief introduction to computational modeling of gene regulatory networks (GRN), followed by a description of our recent results on analysing and synthesising gene regulatory motifs, particularly from the robustness and evolvability perspective. In addition, we demonstrate that robust GRN motifs can emerge from in silico evolution without an explicit selection pressure on robustness and that complex genetic dynamics can be synthesized from simple motifs. Finally, multi-objective reconstruction of a large scale gene regulatory network consisting of 900 genes that is involved in production of antibiotics in bacteria Streptomyces will be presented. We show that the reconstructed model can not only accurately replicate the gene expression time series data, but infer unknown connections between gene as well.
In the second part of the talk, applications of computational models of gene regulatory networks to the self-organization of swarm robots and modeling of morphological development will be given.