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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

72
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
72
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

468
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
468
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

556
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
556
Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

3.0K
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
3.0K
Study Design in Statistics01:15

Study Design in Statistics

8.2K
A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research problem. Statistics is commonly for effective study design and more robust experiments,
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
8.2K
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

272
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
272

You might also read

Related Articles

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

Sort by
Same author

Bayesian fine-mapping pinpoints candidate genes and pleiotropic loci of production traits from a chicken backcrossing scheme.

BMC genomics·2026
Same author

Restructuring breeding programs 2: Assortative mating for improved commercial genetic gain when using optimum contribution selection and diversity introduction.

Genetics, selection, evolution : GSE·2026
Same author

Detection of Parental Reciprocal Translocations via Inter-Chromosomal Linkage Disequilibrium in Offspring Genotypes.

Animal genetics·2026
Same author

Strategies to improve on selection based on estimated breeding values.

Genetics, selection, evolution : GSE·2026
Same author

Impact of erroneous marker data on the accuracy of narrow-sense heritability.

Genetics·2025
Same author

Optimization of recurrent rapid cycle breeding in maize for sustained long-term genetic improvement via stochastic simulations.

G3 (Bethesda, Md.)·2025
Same journal

Duplication-based genetic dissection of the Down syndrome critical region reveals its complex functional organization.

G3 (Bethesda, Md.)·2026
Same journal

The complete sequence of the silkworm W chromosome uncovers its rapid evolution by large-scale duplications/deletions and translocation of W-linked genes.

G3 (Bethesda, Md.)·2026
Same journal

Revisiting the genome assembly of Lupinus species reveals differential diploidization after a shared whole-genome duplication.

G3 (Bethesda, Md.)·2026
Same journal

Deconstructing empirical fitness seascapes across scales of granularity.

G3 (Bethesda, Md.)·2026
Same journal

Genomes of Conopholis americana and Epifagus virginiana: Two holoparasitic plants (Orobanchaceae).

G3 (Bethesda, Md.)·2026
Same journal

"A chromosome-level reference genome for the colonial marine hydrozoan Podocoryna americana".

G3 (Bethesda, Md.)·2026
See all related articles

Related Experiment Video

Updated: Jul 15, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K

Optimization of breeding program design through stochastic simulation with kernel regression.

Azadeh Hassanpour1, Johannes Geibel1,2, Henner Simianer1

  • 1Department of Animal Sciences, Center for Integrated Breeding Research, Animal Breeding and Genetics Group, University of Goettingen, 37075 Goettingen, Germany.

G3 (Bethesda, Md.)
|September 24, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new framework for optimizing complex breeding programs. It uses stochastic simulations and kernel regression to find the best strategy for genetic gain and diversity within budget limits.

Keywords:
genetic gaininbreedingkernel regressionoptimizationresource allocation

More Related Videos

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.8K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K

Related Experiment Videos

Last Updated: Jul 15, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.0K
Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
20:36

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling

Published on: July 4, 2007

8.8K
The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K

Area of Science:

  • Animal Breeding and Genetics
  • Quantitative Genetics
  • Computational Biology

Background:

  • Modern breeding programs face increasing complexity with multiple interdependent parameters and conflicting goals.
  • Resource allocation and strategy optimization are challenging due to this complexity.
  • Current methods often simplify problems by analyzing limited scenarios.

Purpose of the Study:

  • To develop a numerical optimization framework for breeding programs that surpasses simple scenario comparison.
  • To identify optimal breeding strategies by maximizing a target function that balances diverse breeding goals.
  • To define the full space of potential breeding programs within practical constraints like budget and capacity.

Main Methods:

  • Determining the feasible space of breeding programs constrained by budget and housing.
  • Employing stochastic simulations to evaluate the performance of different program parameters.
  • Utilizing kernel regression to handle simulation outcome variability.
  • Iteratively refining the search space to focus on promising areas for optimization.

Main Results:

  • The proposed framework successfully identifies optimal breeding strategies.
  • Demonstrated ability to balance genetic gain and genetic diversity conservation.
  • Effectively operates within defined budget constraints, as shown in a dairy cattle example.

Conclusions:

  • The developed framework offers a robust method for optimizing complex breeding programs.
  • It provides a more comprehensive approach than traditional scenario-based analyses.
  • The method is effective in achieving multiple breeding objectives simultaneously under resource limitations.