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  Topological phenotypes constitute a new dimension in the phenotypic space of leaf venation networks

Ronellenfitsch, H., Lasser, J., Daly, D. C., & Katifori, E. (2015). Topological phenotypes constitute a new dimension in the phenotypic space of leaf venation networks. PLoS Computational Biology, 11(12): e1004680. doi:10.1371/journal.pcbi.1004680.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-5893-7 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002D-5895-3
Genre: Journal Article

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 Creators:
Ronellenfitsch, Henrik1, Author              
Lasser, Jana1, Author              
Daly, Douglas C., Author
Katifori, Eleni1, Author              
Affiliations:
1Max Planck Research Group Physics of Biological Organization, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063293              

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 Abstract: The leaves of angiosperms contain highly complex venation networks consisting of recursively nested, hierarchically organized loops. We describe a new phenotypic trait of reticulate vascular networks based on the topology of the nested loops. This phenotypic trait encodes information orthogonal to widely used geometric phenotypic traits, and thus constitutes a new dimension in the leaf venation phenotypic space. We apply our metric to a database of 186 leaves and leaflets representing 137 species, predominantly from the Burseraceae family, revealing diverse topological network traits even within this single family. We show that topological information significantly improves identification of leaves from fragments by calculating a “leaf venation fingerprint” from topology and geometry. Further, we present a phenomenological model suggesting that the topological traits can be explained by noise effects unique to specimen during development of each leaf which leave their imprint on the final network. This work opens the path to new quantitative identification techniques for leaves which go beyond simple geometric traits such as vein density and is directly applicable to other planar or sub-planar networks such as blood vessels in the brain.

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Language(s): eng - English
 Dates: 2015-12-23
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pcbi.1004680
 Degree: -

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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: 12 Volume / Issue: 11 (12) Sequence Number: e1004680 Start / End Page: - Identifier: ISSN: 1553-734X
CoNE: /journals/resource/1000000000017180_1