Evidence map›Paper›PMID 23180896›Full record

ArticleEvolutionary biology2012

The Measurement of Local Variation in Shape.

Eladio J Márquez, Ryan Cabeen, Roger P Woods, David Houle

Abstract read
In one paragraph

Article in Evolutionary biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Planar morphometrics using Teichmüller maps.Proceedings. Mathematical, physical, and engineering sciences · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Modularity: genes, development and evolution.Annual review of ecology, evolution, and systematics · 2016
    Article
  18. Morphometrics, 3D Imaging, and Craniofacial Development.Current topics in developmental biology · 2015
    Review
  19. Sizing the shape: understanding morphometrics.Journal of clinical and diagnostic research : JCDR · 2015
    Article
  20. The size and shape of the foramen magnum in man.Journal of craniovertebral junction & spine
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Eladio J MárquezDepartment of Biological Science, Florida State University, Tallahassee, FL 32306, USA.
Ryan Cabeen
Roger P Woods
David Houle

Funding

Center for Computational Biology (RMI)U54RR021813 · NCRR · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI TOGA, ARTHUR W · 2004 to 2010
$25.3M
Building, understanding and applying a dictionary of genetic effectsR01GM094424 · NIGMS · FLORIDA STATE UNIVERSITY · PI DWORKIN, IAN MICHAEL, HOULE, DAVID · 2010 to 2013
$1.6M
NCRR NIH HHS U54 RR021813NIGMS NIH HHS R01 GM094424
6 · The paper itself

Abstract

Geometric morphometrics comprises tools for measuring and analyzing shape as captured by an entire set of landmark configurations. Many interesting questions in evolutionary, genetic, and developmental research, however, are only meaningful at a local level, where a focus on "parts" or "traits" takes priority over properties of wholes. To study variational properties of such traits, current approaches partition configurations into subsets of landmarks which are then studied separately. This approach is unable to fully capture both variational and spatial characteristics of these subsets because interpretability of shape differences is context-dependent. Landmarks omitted from a partition usually contain information about that partition's shape. We present an interpolation-based approach that can be used to model shape differences at a local, infinitesimal level as a function of information available globally. This approach belongs in a large family of methods that see shape differences as continuous "fields" spanning an entire structure, for which landmarks serve as reference parameters rather than as data. We show, via analyses of simulated and real data, how interpolation models provide a more accurate representation of regional shapes than partitioned data. A key difference of this interpolation approach from current morphometric practice is that one must assume an explicit interpolation model, which in turn implies a particular kind of behavior of the regions between landmarks. This choice presents novel methodological challenges, but also an opportunity to incorporate and test biomechanical models that have sought to explain tissue-level processes underlying the generation of morphological shape.

Identifiers

PMID23180896
PMCPMC3501737

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.