Literature DB >> 9821492

A simple method for visualization of influential landmarks when using euclidean distance matrix analysis.

T M Cole1, J T Richtsmeier.   

Abstract

Euclidean distance matrix analysis (EDMA) differs from most other morphometric methods for the analysis of landmark coordinate data in that it is coordinate-system invariant. However, strict adherence to coordinate-system invariance (for both biological and statistical reasons) introduces some difficulty in using graphic aids for the analysis and interpretation of EDMA results. We present a simple and effective graphic method to help localize important differences in form, growth, or shape by identifying "influential" landmarks. Examples are presented using simulated data and real data involving both children with craniofacial dysmorphologies and sexual dimorphism in adult Macaca fascicularis.

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Year:  1998        PMID: 9821492     DOI: 10.1002/(SICI)1096-8644(199811)107:3<273::AID-AJPA4>3.0.CO;2-1

Source DB:  PubMed          Journal:  Am J Phys Anthropol        ISSN: 0002-9483            Impact factor:   2.868


  3 in total

1.  Facial asymmetry in young healthy subjects evaluated by statistical shape analysis.

Authors:  Ilker Ercan; Senem Turan Ozdemir; Abdullah Etoz; Deniz Sigirli; R Shane Tubbs; Marios Loukas; Ibrahim Guney
Journal:  J Anat       Date:  2008-12       Impact factor: 2.610

2.  Detecting corpus callosum abnormalities in autism based on anatomical landmarks.

Authors:  Qing He; Ye Duan; Kevin Karsch; Judith Miles
Journal:  Psychiatry Res       Date:  2010-08-30       Impact factor: 3.222

3.  In tumors Salmonella migrate away from vasculature toward the transition zone and induce apoptosis.

Authors:  S Ganai; R B Arenas; J P Sauer; B Bentley; N S Forbes
Journal:  Cancer Gene Ther       Date:  2011-03-25       Impact factor: 5.987

  3 in total

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