Hypergraph geometry reflects higher-order dynamics in protein interaction networks

HIGHLIGHTS

SUMMARY

    Plasticity in gene_expression and thus heterogeneity in interaction dynamics are fundamental in the process of cellular differentiation. For these reasons, a generalized network model is necessary to effectively model higher-order relationships in biological interaction networks. Recent studies have explored weighted PPI network models that incorporate gene-expression measurements as estimates of protein levels to calculate stochastic rates of interaction, allowing quantitative examination of how PPI network dynamics vary with gene_expression in different biological ­settings39-41. The authors then construct a weighted network model by overlaying stochastic weights based on gene_expression measurements of various . . .

     

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