The Visual Analytics cycle applied to Network Medicine. Data from different domains (e.g., cellular, molecular, and genetic networks) are input to two different processes, Visual Data Exploration which exploits visualization paradigms (Node‐Edge, Matrix, Chords, etc.) to represent these data and classic Automated Data Analysis through different approaches (machine learning, network analysis algorithms, etc.). These two processes are interconnected, allowing an analyst to steer algorithms by interacting with the visual representation of results. The whole process generates new insights (e.g., relationships among networks) used as a feedback loop for new cycles of analysis.
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