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

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Distribution and Dispersion00:54

Distribution and Dispersion

Ecology is the study of how organisms interact with their environment and with one another. An important aspect of ecology is understanding where species are found and how individuals are distributed within those areas. The geographic range of a species refers to the total area where its members are located, while dispersion describes the pattern of spacing of individuals within that range.Geographic Range and Dispersion PatternsWithin a species’ geographic range, individuals may be distributed...
Data: Types and Distribution01:19

Data: Types and Distribution

In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).Mechanisms of Genetic VariationThe original sources of genetic variation are mutations,...

You might also read

Related Articles

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

Sort by
Same author

Emergence of network communities driven by local rules.

Physical review. E·2025
Same author

Geometrically balanced model of cell growth.

Journal of theoretical biology·2025
Same author

Inhibition of mitochondrial folate metabolism drives differentiation through mTORC1 mediated purine sensing.

Nature communications·2024
Same author

Robustness and Complexity of Directed and Weighted Metabolic Hypergraphs.

Entropy (Basel, Switzerland)·2023
Same author

HEK293 producing the extracellular domain HER1: Full datasets of continuous fermentation process and metabolites analysis.

Data in brief·2023
Same author

Complex hypergraphs.

Physical review. E·2023

Related Experiment Video

Updated: Jul 17, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Spreading dynamics on heterogeneous populations: multitype network approach.

Alexei Vazquez1

  • 1The Simons Center for Systems Biology, Institute for Advanced Study, Einstein Drive, Princeton, New Jersey 08540, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|February 7, 2007
PubMed
Summary

This study models infectious disease spread in diverse populations using a contact graph and type-network representation. Key findings link outbreak size to the reproductive number matrix

More Related Videos

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Jul 17, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Basics of Multivariate Analysis in Neuroimaging Data
06:35

Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

Following the Dynamics of Structural Variants in Experimentally Evolved Populations
04:52

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Network Science

Background:

  • Infectious disease dynamics are complex in heterogeneous populations.
  • Understanding population structure is crucial for predicting disease spread.

Purpose of the Study:

  • To develop a novel framework for analyzing disease transmission in heterogeneous populations.
  • To provide tools for quantitative prediction of epidemic outbreaks.

Main Methods:

  • Utilized a contact graph to represent population structure.
  • Introduced a type-network representation for the mixing matrix.
  • Derived recursive equations for outbreak size probability distribution.

Main Results:

  • Demonstrated that outbreak size and temporal progression depend on the largest eigenvalue of the reproductive number matrix.
  • Showed the characteristic distance between agents influences epidemic dynamics.
  • Established a link between population structure and disease spread metrics.

Conclusions:

  • The type-network approach offers intuitive insights into mixing patterns.
  • The study provides a method for both qualitative understanding and quantitative prediction of epidemic spread.
  • Findings can inform the design of effective intervention strategies.