The Computational Network Imaging Frontier: Relevance for Digital Biomarkers in Precision Oncology.

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Cancer treatment is no doubt the greatest of the big challenges in the newborn field of Precision Medicine. As an effect of advances in imaging technologies and methods, the assessment of
therapeutic response in cancer patients now involves a mix of qualitative and quantitative aspects, thus calling for integrative approaches linking together various types of evidences obtained from
molecular profiling, cell signaling, experimental omics and clinical records. Such multiplexing gives origin to a multitude of data, presenting an unprecedented opportunity for building multilevel inference algorithms targeted to cancer therapy. We describe a network-driven methodology and the rationale that leverages the plasticity and adaptability of possible configurations and its representative power.

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