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At a first glance, genomics has not produced a strong conceptual change in biology. The fundamental problems remain: understanding the origin of life, the complex organization of a cell, the pathways of differentiation, aging, and the molecular and cellular bases for the capabilities of the brain. Genomics may really be opening the door to a more profound conceptual change in the way we study living systems in the laboratory. This is an area of computational biology that welcomes new methods, ideas, and approaches with the goal of generating a better understanding of the complex networks of metabolic and regulatory capabilities of the cell . Classical concepts have to be redefined or clarified to address the study of the genetics of populations and of the biochemical interactions and regulatory networks organizing a living system. The first chapter,is an exercise in thinking about the concept of homology (the common origin of similarities) in order to use it adequately when considering homologous networks of gene regulation between species. The second chapter describes an integrated system for this task. Databases centering on specific signals, motifs, or structures have exploded in number in the last years. The third chapter, shows a system capable of integrating data from different databases, and its subsequent use in the integration and modeling of metabolic pathways using a rule-based system. chapter 4,describes the foundations of weight matrices and their biophysical interpretation in protein-DNA interactions. Chapter 5,is devoted to computational studies of gene regulation in E. coli in which different pieces are put together, making it feasible to think of a global computational study of a complete network of transcription initiation in a cell. chapter 6,show how the integration of gene regulation has to be supported by experimental studies of transcriptome analyses combined with computational motif searches. chapter 7 and chapter 8, A pair of chapters illustrate the complexity of these issues when studying eukaryotes, as seen in the signal transduction modeling and by the Boolean network methodology and its plausible application to modeling the network of factors involved in the biology of asthma' chapter 9 presents a relatively novel approach using phylogenetic profiles to define a quantitative definition of function in genomics. The book ends with a chapter that describes a more ambitious modeling that integrates metabolism, regulation, translation, and membrane transport.