Core motifs predict dynamic attractors in combinatorial threshold-linear networks

HIGHLIGHTS

• who: Caitlyn Parmelee and collaborators from the Mathematics, University of North Carolina at Chapel Hill, State College, PA, United States of have published the article: Core motifs predict dynamic attractors in combinatorial threshold-linear networks, in the Journal: PLOS ONE of 26/09/2021
• what: In the Supporting Information, the authors provide a complete dictionary of all the oriented graphs with no sources and sinks, together with their corresponding attractors and sequences. The authors have shown that in the case of CTLNs, the problem is surprisingly tractable. The authors focused on oriented graphs with no . . .
  

   

  

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