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Structural Systems Biology

Much of systems biology aims to predict the behaviour of biological systems on the basis of the set of molecules involved. Understanding the interactions between these molecules is therefore crucial to such efforts. Although many thousands of interactions are known, precise molecular details are available for only a tiny fraction of them. The difficulties that are involved in experimentally determining atomic structures for interacting proteins by conventional technology make predictive computational methods essential. Structural details can ultimately turn abstract system representations into models that more accurately reflect biological reality. On the systems level, experimental approaches to analyze and map the molecular interactions and pathways at a greater scale may be eventually derived from the current state of cryo-electron microscopy and machine learning technology. These investigations may also benefit tremendously from the high-performance computing technology that would practically scale up the magnitude of data and problems to be handled at a time. In the Intel® PCCSB and its collaborative laboratories, scientists are working toward the understanding of biological systems in unprecedented structural detail. Novel mathematical models and machine learning algorithms, along with experimental methods, are being developed to provide a four-dimensional atlas of the life cycle of cells.