| Sumario: | "Systems biology combines biological, mathematical, computational, and physical sciences in order to analyze, model, and create biological systems. To this end, biological knowledge is often extracted from high-throughput "omics" (genomics, transcriptomics, proteomics, metabonomics, etc.) data that is generated via next-generation molecular technologies. The core of systems biology consists in turning data into networks to which we want to give a dynamic This book overviews state-of-the-art techniques, and introduces related tools and practices, to formalize models and automate reasoning for systems biology. The authors present and compare the main formal methods used in systems biology for modelling biological networks, including discussion of their advantages / drawbacks and main applications. Among the methods covered are Boolean networks, systems biology markup language (SBML), linear logic, differential equations, and automata"--
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