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The ability to sequence the genome of entire organisms has produced a fundamental change in the scientific practice of the life sciences. With the Omics revolution, biologists working with cellular systems have become dependent on the support of and collaboration with other disciplines. Following the identification and characterization of cellular components in the context of bioinformatics, the focus has shifted in recent years to the study of mechanisms that determine the functioning of cells in terms of gene regulatory networks, signal transduction and metabolic pathways. This shift of focus towards an understanding of functional activity and therefore towards cellular processes required methodologies from systems theory and thus expertise from other fields than computer science and physics. Since then, the term 'systems biology" has become associated with an interdisciplinary approach that realizes a practice of data-driven modelling and model-driven experimentation. With systems biology, mathematical models have become a central element in the formulation of biological arguments and as a consequence, a new quality of interdisciplinary collaboration has become necessary. The "modeller" or "theoretician" no longer plays a simple supportive role. Instead, the construction and analyses of the models require both – the "experimentalist" and "modeller" to meet at "eye level", pursue a common question, and rely upon each other. The present text discusses the practice of systems biology with respect to the hurdles and opportunities provided by interdisciplinary collaborations in this field. The main conclusion is that truly interdisciplinary collaborative efforts are a necessity for progress in the life sciences but these efforts are hampered by academic structures and practices that prevent these projects from succeeding.

DOI: 10.1007/978-94-007-5845-2_18

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