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Evolution of gene regulated cellular growth models for morphological and neural development

Prof. Dr.-Ing. Yaochu Jin ( Head of the Nature-Inspired Computing and Engineering (NICE) Group, Department of Computing, University of Surrey, UK )

This talk presents a cellular growth model governed by gene regulatory networks for simulating neural and morphological growth. With this model, we first empirically show that development is key to resolve the trade- off in robustness and evolvability. We then evolve in silico the gene regulatory networks to achieve desired regulatory dynamics for neural development as well as for stable cell growth and regeneration. It is demonstrated that dynamically stable growth can be achieved in the developmental process, where cell proliferation and cell apoptosis reach an equilibrium. Our results also indicate that stable growth and regeneration can be evolved only if selection pressure is present during the development. Finally, we examine the network motifs responsible for stable growth and regeneration that emerged from evolution. It is found that the number of most motifs increases in the beginning of evolution and decreases later on as the evolution proceeds. This suggests that a certain degree of redundancy improves evolvability, however, motifs that are not used for the targeted development will get lost later on.



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