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This book compiles progress on gene regulatory network (GRN) research, focusing particularly on different domains that apply evolutionary algorithms (EAs) as the computational methodology. These areas are the analysis of gene expression data to discover knowledge; the reconstruction of GRN from expression profiles; and the evolution of GRN for target behavior. The book also presents uses of GRN with EAs in applications such as architectural design, agent control and robotics.A ‘preliminaries’ part introduces GRN to readers with a computer science background, and EAs to readers with a life science background. The authors present the EA approaches for analysis of gene expression data. Next, readers are guided step-by-step through the reverse engineering and evolution of GRN using EAs. Topics covered include deterministic and stochastic modelling of GRN, time series data analysis, single and multi-objective genetic algorithms, and swarm intelligence.The last part of the book focuses on future applications of GRN with use of EAs, in the fields of agent control, robotics, and design. The fifteen chapters are authored by well-known researchers and experienced practitioners in their respective fields.