Evolutionary Computation in Gene Regulatory Network Research

PREFACE

Since the identification of regulatory sequences associated with genes in the 1960s, the research in the field of gene regulatory network (GRN) is ever increasing—not only for understanding the dynamics of these complex systems but also for uncovering how they control the development, behavior, and fate of biological organisms. Dramatic progress is being made in understanding gene networks of organisms, thanks to the recent revival of evolutionary developmental biology (evo-devo). For example, there have been many startling discoveries regarding the Hox genes (master control genes that define segment structures in most metazoa). At the same time, neuroscientists and evolutionary biologists think that the modularity of gene networks (combination of functionally related structures and separation of unrelated structures) is crucial to the development of complex structures.

Gene control network, which is a representative concept in the evo-devo approach, is considered to be the central process that achieves the functionality of a molecular machine (flow of DNA-RNA-protein-metabolite) and models interactions between genes. Therefore, analysis of gene networks may provide insights into the fundamental mechanisms of life phenomena. These include robustness and possibility of evolution—two mechanisms have been observed at various levels of organisms, from gene control to fitness value of an organism. Stuart Kauffman used the random Boolean graph model to experimentally prove ...