The Concept of Morphospaces in Evolutionary and Developmental Biology: Mathematics and Metaphors
By P. Mitteroecker, Simon M. Huttegger. 2009
135 citations recorded by the source corpus.
Subfields: Geometry and Topology, Paleontology
View Paper: https://www.semanticscholar.org/paper/8698abdb8d2ed0d5b783a2c70ba37b0f4b89c0dc
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geometry and Topology
- P. Gunz
- P. Mitteroecker
- Dean C. Adams
- Sonja Windhager
- Katrin Schaefer
- M. Collyer
- C. Klingenberg
- Dean C. Adams
In Paleontology
- P. Mitteroecker
- P. Gunz
- Dean C. Adams
- Sonja Windhager
- Katrin Schaefer
- M. Collyer
- Dean C. Adams
- C. Klingenberg
Citations in the corpus
- Combining Geometric Morphometrics and Finite Element Analysis with Evolutionary Modeling: Towards a Synthesis (2016, unknown): “2; Rohlf, 1993; Mardia and Dryden, 1998; Mitteroecker and Huttegger, 2009).”
- Linear Discrimination, Ordination, and the Visualization of Selection Gradients in Modern Morphometrics (2011, unknown): “distance—are affine invariant (Huttegger and Mitteroecker, submitted; Mitteroecker and Huttegger 2009).”
- A brief review of shape, form, and allometry in geometric morphometrics, with applications to human facial morphology (2013, background): “Shape space and form space Mathematical spaces are widely used in the sciences to represent relationships between complex objects (e.g., Stadler et al. 2001; Mitteroecker and Huttegger 2009).”
- Phylogenetic Comparative Methods and the Evolution of Multivariate Phenotypes (2019, background): “…geometry is appropriate for the span of phenotypic values in the data space also implies that distances and directions between specimens confer biological meaning, and comparisons of such measures are interpretable (see discussion in Huttegger & Mitteroecker 2011, Mitteroecker & Huttegger 2009).”
- Advances in Geometric Morphometrics (2009, methodology): “Multivariate regression of the shape variables on an external variable (shape regression) is the method of choice to assess the influence of a single factor such as a functional or environmental variable, age, or the dose of a drug on shape (Bookstein 1991; Monteiro 1999).”