Literature DB >> 1638259

Tree asymmetry--a sensitive and practical measure for binary topological trees.

J Van Pelt1, H B Uylings, R W Verwer, R J Pentney, M J Woldenberg.   

Abstract

The topological structure of a binary tree is characterized by a measure called tree asymmetry, defined as the mean value of the asymmetry of its partitions. The statistical properties of this tree-asymmetry measure have been studied using a growth model for binary trees. The tree-asymmetry measure appears to be sensitive for topological differences and the tree-asymmetry expectation for the growth model that we used appears to be almost independent of the size of the trees. These properties and the simple definition make the measure suitable for practical use, for instance for characterizing, comparing and interpreting sets of branching patterns. Examples are given of the analysis of three sets of neuronal branching patterns. It is shown that the variance in tree-asymmetry values for these observed branching patterns corresponds perfectly with the variance predicted by the used growth model.

Mesh:

Year:  1992        PMID: 1638259     DOI: 10.1007/bf02459929

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  9 in total

1.  Analysis of binary trees when occasional multifurcations can be considered as aggregates of bifurcations.

Authors:  R W Verwer; J Van Pelt
Journal:  Bull Math Biol       Date:  1990       Impact factor: 1.758

2.  Branching ratio and growth of tree-like structures.

Authors:  K Horsfield; M J Woldenberg
Journal:  Respir Physiol       Date:  1986-01

3.  Application of growth models to the topology of neuronal branching patterns.

Authors:  J van Pelt; R W Verwer; H B Uylings
Journal:  J Neurosci Methods       Date:  1986-10       Impact factor: 2.390

4.  Sequential and synchronous growth models related to vertex analysis and branching ratios.

Authors:  K Horsfield; M J Woldenberg; C L Bowes
Journal:  Bull Math Biol       Date:  1987       Impact factor: 1.758

5.  Topological properties of binary trees grown with order-dependent branching probabilities.

Authors:  J Van Pelt; R W Verwer
Journal:  Bull Math Biol       Date:  1986       Impact factor: 1.758

6.  Descriptive and comparative analysis of geometrical properties of neuronal tree structures.

Authors:  R W Verwer; J van Pelt
Journal:  J Neurosci Methods       Date:  1986-10       Impact factor: 2.390

7.  A new method for the topological analysis of neuronal tree structures.

Authors:  R W Verwer; J van Pelt
Journal:  J Neurosci Methods       Date:  1983-08       Impact factor: 2.390

8.  Growth models (including terminal and segmental branching) for topological binary trees.

Authors:  J Van Pelt; R W Verwer
Journal:  Bull Math Biol       Date:  1985       Impact factor: 1.758

9.  The exact probabilities of branching patterns under terminal and segmental growth hypotheses.

Authors:  J Van Pelt; R W Verwer
Journal:  Bull Math Biol       Date:  1983       Impact factor: 1.758

  9 in total
  27 in total

1.  Synaptic reorganization induced by selective photoablation of an identified neuron.

Authors:  A Mizrahi; F Libersat
Journal:  J Neurosci       Date:  2001-12-01       Impact factor: 6.167

2.  The DIADEM metric: comparing multiple reconstructions of the same neuron.

Authors:  Todd A Gillette; Kerry M Brown; Giorgio A Ascoli
Journal:  Neuroinformatics       Date:  2011-09

3.  Morphological homeostasis in cortical dendrites.

Authors:  Alexei V Samsonovich; Giorgio A Ascoli
Journal:  Proc Natl Acad Sci U S A       Date:  2006-01-17       Impact factor: 11.205

4.  Mathematical foundations of the dendritic growth models.

Authors:  José A Villacorta; Jorge Castro; Pilar Negredo; Carlos Avendaño
Journal:  J Math Biol       Date:  2007-07-24       Impact factor: 2.259

Review 5.  On comparing neuronal morphologies with the constrained tree-edit-distance.

Authors:  Todd A Gillette; John J Grefenstette
Journal:  Neuroinformatics       Date:  2009-07-28

6.  Tiling among stereotyped dendritic branches in an identified Drosophila motoneuron.

Authors:  F Vonhoff; C Duch
Journal:  J Comp Neurol       Date:  2010-06-15       Impact factor: 3.215

7.  An efficient and extendable python library to analyze neuronal morphologies.

Authors:  Benjamin Torben-Nielsen
Journal:  Neuroinformatics       Date:  2014-10

8.  Neuritic growth rate described by modeling microtubule dynamics.

Authors:  M P Van Veen; J Van Pelt
Journal:  Bull Math Biol       Date:  1994-03       Impact factor: 1.758

9.  Measuring neuronal branching patterns using model-based approach.

Authors:  Artur Luczak
Journal:  Front Comput Neurosci       Date:  2010-10-20       Impact factor: 2.380

10.  Requirement of TrkB for synapse elimination in developing cerebellar Purkinje cells.

Authors:  Laurens W J Bosman; Jana Hartmann; Jaroslaw J Barski; Alexandra Lepier; Michael Noll-Hussong; Louis F Reichardt; Arthur Konnerth
Journal:  Brain Cell Biol       Date:  2007-03-01
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