Emergence of feedback in artificial gene regulatory networks

In this paper, we present a model for simulating the evolution of development together with a method for the analysis of emergence of negative feedback inside the regulatory network. In order to record the development of feedback during evolution, we analyze both the static as well as the dynamic interactions between the transcription factors in the regulatory network. When perturbing the gene regulatory network using random mutations, we find that the evolved negative feedback is the main mechanism for robustness against such mutations. We argue that this robustness is the reason for the sustained emergence of negative feedback during evolution.

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Till Steiner, Lisa Schramm, Yaochu Jin, Bernhard Sendhoff
• Keywords: Artificial Intelligence, CEC 2007, Evolved Negative Feedback, Negative Feedback, Regulatory Network