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Systems biology is an emerging discipline that studies the underlying network structure and the dynamics of metabolism, cells or whole organisms. It aims to investigate all interacting components simultaneously and requires data from high throughput techniques. These data from the "omic" sciences are computed and used to build in silico models of biological systems that ultimately will prove to be an invaluable tool in drug development.
This book brings together the various fields of functional genomics and systems biology that provide information on metabolic function with a special emphasis on the identification of drug targets. It includes practical examples from the various "omic" sciences as well as theoretical examples of how integrated knowledge of these sciences can be applied to drug discovery. It is of interest to researchers in the pharmaceutical drug discovery environment, as well as those in the academic field with an interest in the functional application of the "omic" sciences.
Systems biology and its impact on anti-infective drug development.- Applications of transcriptional profiling in antibiotics discovery and development.- Chemical genetics: An evolving toolbox for target identification and lead optimization.- Proteomic profiling of cellular stresses in Bacillus subtilis reveals cellular networks and assists in elucidating antibiotic mechanisms of action.- Elucidating the mode-of-action of compounds from metabolite profiling studies.- A subsystems-based approach to the identification of drug targets in bacterial pathogens.- Metabolic control analysis to identify optimal drug targets.- The protein network as a tool for finding novel drug targets.- Toxicogenomics applied to predictive and exploratory toxicology for the safety assessment of new chemical entities: a long road with deep potholes.- The application of the theory of biological robustness to complex host-pathogen systems .- Toward whole cell modeling and simulation: comprehensive functional genomics through the constraint-based approach.- Genomics of host-pathogen interactions