• DocumentCode
    1191199
  • Title

    Quantifying the Degree of Self-Nestedness of Trees: Application to the Structural Analysis of Plants

  • Author

    Godin, Christophe ; Ferraro, Pascal

  • Author_Institution
    INRIA Project-Team Virtual Plants, CIRAD, Montpellier, France
  • Volume
    7
  • Issue
    4
  • fYear
    2010
  • Firstpage
    688
  • Lastpage
    703
  • Abstract
    In this paper, we are interested in the problem of approximating trees by trees with a particular self-nested structure. Self-nested trees are such that all their subtrees of a given height are isomorphic. We show that these trees present remarkable compression properties, with high compression rates. In order to measure how far a tree is from being a self-nested tree, we then study how to quantify the degree of self-nestedness of any tree. For this, we define a measure of the self-nestedness of a tree by constructing a self-nested tree that minimizes the distance of the original tree to the set of self-nested trees that embed the initial tree. We show that this measure can be computed in polynomial time and depict the corresponding algorithm. The distance to this nearest embedding self-nested tree (NEST) is then used to define compression coefficients that reflect the compressibility of a tree. To illustrate this approach, we then apply these notions to the analysis of plant branching structures. Based on a database of simulated theoretical plants in which different levels of noise have been introduced, we evaluate the method and show that the NESTs of such branching structures restore partly or completely the original, noiseless, branching structures. The whole approach is then applied to the analysis of a real plant (a rice panicle) whose topological structure was completely measured. We show that the NEST of this plant may be interpreted in biological terms and may be used to reveal important aspects of the plant growth.
  • Keywords
    biocomputing; botany; computational complexity; data compression; NEST; compression coefficients; nearest embedding self-nested tree; plant branching structure analysis; polynomial time; self-nested tree structure; trees approximation; Computer architecture; Databases; Digital audio players; Embryo; Noise level; Organisms; Pattern recognition; Plants (biology); Polynomials; Time measurement; Tree reduction; branching structures; differentiation state.; meristem; plant architecture; self-similarity; tree compression; tree-to-tree edit distance; Algorithms; Databases, Genetic; Evolution, Molecular; Phylogeny; Plants;
  • fLanguage
    English
  • Journal_Title
    Computational Biology and Bioinformatics, IEEE/ACM Transactions on
  • Publisher
    ieee
  • ISSN
    1545-5963
  • Type

    jour

  • DOI
    10.1109/TCBB.2009.29
  • Filename
    4799769