Dynamic Influence Networks for Rule-Based Models

  title={Dynamic Influence Networks for Rule-Based Models},
  author={Angus Graeme Forbes and Andrew Burks and Kristine Lee and Xing Li and Pierre Boutillier and Jean Krivine and Walter Fontana},
  journal={IEEE Transactions on Visualization and Computer Graphics},
  • A. ForbesA. Burks W. Fontana
  • Published 2 November 2017
  • Computer Science, Biology
  • IEEE Transactions on Visualization and Computer Graphics
We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigate the combinatorial complexity of multi-state and multi-component biological molecules. Our technique visualizes the dynamics of these rules as they evolve over time. Using the… 

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