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Hierarchical Ordering of Reticular Networks

Author

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  • Yuriy Mileyko
  • Herbert Edelsbrunner
  • Charles A Price
  • Joshua S Weitz

Abstract

The structure of hierarchical networks in biological and physical systems has long been characterized using the Horton-Strahler ordering scheme. The scheme assigns an integer order to each edge in the network based on the topology of branching such that the order increases from distal parts of the network (e.g., mountain streams or capillaries) to the “root” of the network (e.g., the river outlet or the aorta). However, Horton-Strahler ordering cannot be applied to networks with loops because they they create a contradiction in the edge ordering in terms of which edge precedes another in the hierarchy. Here, we present a generalization of the Horton-Strahler order to weighted planar reticular networks, where weights are assumed to correlate with the importance of network edges, e.g., weights estimated from edge widths may correlate to flow capacity. Our method assigns hierarchical levels not only to edges of the network, but also to its loops, and classifies the edges into reticular edges, which are responsible for loop formation, and tree edges. In addition, we perform a detailed and rigorous theoretical analysis of the sensitivity of the hierarchical levels to weight perturbations. In doing so, we show that the ordering of the reticular edges is more robust to noise in weight estimation than is the ordering of the tree edges. We discuss applications of this generalized Horton-Strahler ordering to the study of leaf venation and other biological networks.

Suggested Citation

  • Yuriy Mileyko & Herbert Edelsbrunner & Charles A Price & Joshua S Weitz, 2012. "Hierarchical Ordering of Reticular Networks," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-9, June.
  • Handle: RePEc:plo:pone00:0036715
    DOI: 10.1371/journal.pone.0036715
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    Cited by:

    1. Marc Barthelemy, 2017. "From paths to blocks: New measures for street patterns," Environment and Planning B, , vol. 44(2), pages 256-271, March.
    2. Elif Tekin & David Hunt & Mitchell G Newberry & Van M Savage, 2016. "Do Vascular Networks Branch Optimally or Randomly across Spatial Scales?," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-28, November.
    3. Mitchell G Newberry & Daniel B Ennis & Van M Savage, 2015. "Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-18, August.
    4. Henrik Ronellenfitsch & Jana Lasser & Douglas C Daly & Eleni Katifori, 2015. "Topological Phenotypes Constitute a New Dimension in the Phenotypic Space of Leaf Venation Networks," PLOS Computational Biology, Public Library of Science, vol. 11(12), pages 1-12, December.

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