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A Generalized Approach to the Modeling and Analysis of 3D Surface Morphology in Organisms

Overview of attention for article published in PLOS ONE, October 2013
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Title
A Generalized Approach to the Modeling and Analysis of 3D Surface Morphology in Organisms
Published in
PLOS ONE, October 2013
DOI 10.1371/journal.pone.0077551
Pubmed ID
Authors

Janice L. Pappas, Daniel J. Miller

Abstract

The surface geometry of an organism represents the boundary of its three-dimensional (3D) form and can be used as a proxy for the phenotype. A mathematical approach is presented that describes surface morphology using parametric 3D equations with variables expressed as x, y, z in terms of parameters u, v. Partial differentiation of variables with respect to parameters yields elements of the Jacobian representing tangent lines and planes of every point on the surface. Jacobian elements provide a compact size-free summary of the entire surface, and can be used as variables in principal components analysis to produce a morphospace. Mollusk and echinoid models are generated to demonstrate that whole organisms can be represented in a common morphospace, regardless of differences in size, geometry, and taxonomic affinity. Models can be used to simulate theoretical forms, novel morphologies, and patterns of phenotypic variation, and can also be empirically-based by designing them with reference to actual forms using reverse engineering principles. Although this study uses the Jacobian to summarize models, they can also be analyzed with 3D methods such as eigensurface, spherical harmonics, wavelet analysis, and geometric morphometrics. This general approach should prove useful for exploring broad questions regarding morphological evolution and variation.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Turkey 1 2%
Vietnam 1 2%
Brazil 1 2%
New Zealand 1 2%
United States 1 2%
Unknown 45 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Ph. D. Student 12 24%
Student > Doctoral Student 5 10%
Student > Bachelor 5 10%
Student > Master 3 6%
Other 8 16%
Unknown 3 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 41%
Earth and Planetary Sciences 10 20%
Computer Science 3 6%
Engineering 3 6%
Mathematics 2 4%
Other 7 14%
Unknown 5 10%