Theodore M. Cole
University of Missouri–Kansas City
24 Papers
263 Citations
Theodore M. Cole is an academic researcher from University of Missouri–Kansas City. The author has contributed to research in topics: Craniosynostosis & Trisomy. The author has an hindex of 17, co-authored 24 publications. Previous affiliations of Theodore M. Cole include Johns Hopkins University School of Medicine & State University of New York System.
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Papers
Phenotypic integration of neurocranium and brain.
Joan T. Richtsmeier,Joan T. Richtsmeier,Kristina Aldridge,Valerie B. DeLeon,Jayesh Panchal,Alex A. Kane,Alex A. Kane,Jeffrey L. Marsh,Jeffrey L. Marsh,Peng Yan,Theodore M. Cole +10 more
TL;DR: A comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skulls are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture.
Postnatal heterochrony of the masticatory apparatus in Cebus apella and Cebus albifrons
TL;DR: It is concluded that the modifications for hard-object feeding seen in C. apella adults are most probably the result of selection on prenatal growth processes.
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Capturing data from three-dimensional surfaces using fuzzy landmarks.
TL;DR: This study defines a new class of landmarks, termed fuzzy landmarks, that will allow us to represent the form of the neurocranium, and presents a test case in which the cranial bosses are evaluated as fuzzy landmarks.
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Taxonomic affinity of the early Homo cranium from Swartkrans, South Africa.
TL;DR: The linkage of SK 847 to KNM-ER 1813, and especially Stw 53, suggests that the Swartkrans cranium may have its closest affinity with H. habilis sensu lato.
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A parametric bootstrap approach to the detection of phylogenetic signals in landmark data
Theodore M. Cole,Subhash R. Lele,Joan T. Richtsmeier +2 more
- 01 Jan 2003
TL;DR: A new method for detecting phylogenetic signals when form is described using landmark coordinate data is presented, and a parametric bootstrapping algorithm that, while applied to landmarks, is general enough to be applied to any sort of morphometric data where a reasonable model of within-sample variation can be specified.
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