Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

A Practical Guide to Phylogenetics for Nonexperts12:00

A Practical Guide to Phylogenetics for Nonexperts

36.0K
Here we describe a step-by-step pipeline for generating reliable phylogenies from nucleotide or amino acid sequence datasets. This guide aims to serve researchers or students new to phylogenetic...
36.0K
Trait and State Self-Esteem02:08

Trait and State Self-Esteem

11.4K
The term self-esteem is often used generically, to refer to how people feel about themselves. However, according to research, there are three distinct constructs that should not be used interchangeably (Brown & Marshall, 2006). 
11.4K
Polygenic Traits01:18

Polygenic Traits

68.9K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
68.9K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

16.4K
A method of constructing a phylogenetic tree based on sequence homology of SWEETs from eukaryotes and SemiSWEETs from prokaryotes is described. Phylogenetic analysis is a useful tool for explaining the evolutionary relatedness between homologous proteins or genes from different organism...
16.4K
Multiple Allele Traits01:49

Multiple Allele Traits

38.0K
The Concept of Multiple Allelism
38.0K
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

11.6K
This article focuses on the identification of high-confident interaction datasets between host and pathogen proteins using a combination of two orthogonal methods: yeast two-hybrid followed by a high-throughput interaction assay in mammalian cells called...
11.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same authorSame journal

An Empirical Bayes approach for the study of phenotypic evolution from high-dimensional data.

Systematic biology·2026
Same author

Phylogenetic Patterns and Genomic Correlates of Pronounced Neocortical Reduction in New World Monkeys.

Brain, behavior and evolution·2026
Same author

Integrating Earth history into phylogenetic diversification models.

Trends in ecology & evolution·2026
Same author

Evolution of a trait distributed over a large fragmented population: propagation of chaos meets adaptive dynamics.

Journal of mathematical biology·2026
Same author

Integrating fossils samples with heterogeneous diversification rates: a combined Multi-Type Fossilized Birth-Death model.

Systematic biology·2026
Same author

Parallel Genomic Remodelling Associated With Independent Terrestrialization Events in Arthropods.

Molecular ecology·2025

Related Experiment Video

Updated: Jan 19, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.0K

Characterizing and Comparing Phylogenetic Trait Data from Their Normalized Laplacian Spectrum.

Eric Lewitus1,2, Leandro Aristide1, Hélène Morlon1

  • 1Ecole Normale Superieure Paris Sciences et Lettres (PSL) Research University, Institut de Biologie de l'Ecole Normale Superieure (IBENS) CNRS UMR 8197 INSERM U1024 46rue d'Ulm,F-75005, Paris, France.

Systematic Biology
|September 19, 2019
PubMed
Summary

This study introduces a new nonparametric framework using the phylogenetic spectral density profile (SDP) to analyze phenotypic evolution. The SDP method effectively clusters trait data and visualizes evolutionary patterns across species.

Keywords:
Laplacianmacroevolutionphylogeneticsprimatestanagerstraits

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.4K
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.6K

Related Experiment Videos

Last Updated: Jan 19, 2026

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

36.0K
Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
08:57

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

16.4K
A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
13:56

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Published on: July 18, 2013

11.6K

Area of Science:

  • Evolutionary biology
  • Phylogenetics
  • Biodiversity science

Background:

  • Understanding phenotypic evolution is key to biodiversity.
  • Existing methods lack a comprehensive nonparametric framework for trait evolution analysis.
  • Phylogenetic spectral density profile (SDP) has been used for diversification patterns.

Purpose of the Study:

  • To provide a nonparametric framework for analyzing phylogenetic trait data using SDP.
  • To demonstrate the utility of SDP for characterizing and comparing phenotypic evolution patterns.
  • To offer a tool for big data analyses in evolutionary biology.

Main Methods:

  • Constructing the SDP of trait data from the normalized graph Laplacian.
  • Applying SDP to simulated data for clustering and pattern characterization.
  • Utilizing SDP for visualization of phenotypic space and model distinguishability.

Main Results:

  • SDP successfully clusters phylogenetic trait data into meaningful groups.
  • SDP characterizes phenotypic patterning within these groups.
  • SDP aids in visualizing phenotypic space and assessing trait evolution models.

Conclusions:

  • The SDP framework offers a powerful, nonparametric approach to analyzing phenotypic evolution.
  • This method is applicable to diverse datasets, including morphometric and molecular data.
  • SDP is expected to benefit big data analyses in evolutionary biology.