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SAveRUNNER: A network-based algorithm for drug repurposing and its application to COVID-19

Fig 8

SAveRUNNER algorithm.

SAveRUNNER encompasses six steps: (1–3) compute a weighted bipartite drug-disease network, where nodes are both drugs and diseases, edges are proximal drug-disease associations (z-score proximity ≤ selected threshold), and weights are either the proximity or similarity measure; (4–6) compute the normalized adjusted similarity measure to correct the weights of the drug-disease network and to prioritize the predicted drug-disease associations. Legend: QC is the quality cluster score; Win is the total weight of edges within each cluster; Wout is the total weight of edges connecting each cluster to the rest of network; P is the node density within each cluster; c and d parameters are the sigmoid steepness and midpoint, respectively.

Fig 8

doi: https://doi.org/10.1371/journal.pcbi.1008686.g008