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Gene regulatory networks (GRNs) are complex control systems that govern the interaction of genes, which ultimately control cellular processes at the protein level. GRNs can be represented using abstract models such as random Boolean networks (RBNs), where gene activities and their interactions are captured as nodes with associated Boolean functions, which receive activation or repressor signals from other nodes. We have developed an evolutionary model of gene regulatory networks using RBNs todoi:10.1145/1389095.1389150 dblp:conf/gecco/EsmaeiliJ08 fatcat:zcxexk3otje4plcj4vvhz6mcdu