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

Rate-Determining Steps03:08

Rate-Determining Steps

36.8K
Relating Reaction Mechanisms
In a multistep reaction mechanism, one of the elementary steps progresses significantly slower than the others. This slowest step is called the rate-limiting step (or rate-determining step). A reaction cannot proceed faster than its slowest step, and hence, the rate-determining step limits the overall reaction rate.
The concept of rate-determining step can be understood from the analogy of a 4-lane freeway with a short-stretch of traffic-bottleneck caused due to...
36.8K
High-Level and Low-Level Awareness01:19

High-Level and Low-Level Awareness

631
Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
631
Leveling Effect01:29

Leveling Effect

1.4K
In acid-base chemistry, the leveling effect refers to the limitation imposed by the solvent on the strength of acids and bases in solution. When a base stronger than the solvent's conjugate base is used, it deprotonates the solvent until the base is entirely consumed, making it ineffective against weaker acids. Conversely, an acid stronger than the solvent's conjugate acid protonates the solvent until the acid is depleted, rendering it ineffective against weaker bases. Essentially, the...
1.4K
Levels of Organization01:09

Levels of Organization

139.0K
Biological organization is the classification of biological structures, ranging from atoms at the bottom of the hierarchy to the Earth's biosphere. Each level of the hierarchy represents an increase in complexity that builds upon the previous level.
Molecules Are Composed of Atoms, and Biomolecules Are Assembled from Molecules:
The most basic levels include atoms, molecules, and biomolecules. Atoms, the smallest unit of ordinary matter, are composed of a nucleus and electrons. Molecules...
139.0K
Fermi Level01:18

Fermi Level

1.7K
The Fermi-Dirac function is represented by an S-shaped curve indicating the probability of an energy state being occupied by an electron at a given temperature. The Fermi level is the energy level at which there is a fifty percent chance of finding an electron, and it is positioned between the lower-energy valence band and the higher-energy conduction band.
At absolute zero temperature, electrons fill all energy states up to the Fermi level, leaving upper states empty. As the temperature rises,...
1.7K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

498
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
498

You might also read

Related Articles

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

Sort by
Same authorSame journal

Determining crossover count and position in two pig lines with different selection histories.

Genetics, selection, evolution : GSE·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

Methods to Detect Selection History in a Population under Ongoing Directional Selection.

Genetics·2026
Same author

Unravelling the Genetic Structure of Local and Mainstream Red-Pied Cattle Breeds Using Genomics and Extended Pedigree Analysis.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie·2026
Same author

Restructuring breeding programs 1: Integration of diversity.

Genetics, selection, evolution : GSE·2026
Same author

Targeted Allele Frequency Tuning (TAFT) in breeding populations via alternative optimum contribution selection.

Genetics·2026
Same journal

The mitogenome diversity of Alpine Rendena cattle: new clues on its maternal origin and the complex substructure of haplogroup T3.

Genetics, selection, evolution : GSE·2026
Same journal

Genomic partitioning and functional dissection of inbreeding depression for stature in Brown Swiss cattle.

Genetics, selection, evolution : GSE·2026
Same journal

Modest contribution of metabolomic data to genomic prediction of breeding values for feed conversion ratio in pigs.

Genetics, selection, evolution : GSE·2026
Same journal

Effect of methylation on genome mutability in cattle.

Genetics, selection, evolution : GSE·2026
Same journal

Genomic selection strategies and their potential to maintain rare alleles and de-novo mutations: a long-term assessment.

Genetics, selection, evolution : GSE·2026
See all related articles

Related Experiment Video

Updated: Jan 23, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.5K

A second-level diagonal preconditioner for single-step SNPBLUP.

Jeremie Vandenplas1, Mario P L Calus2, Herwin Eding3

  • 1Animal Breeding and Genomics, Wageningen UR, P.O. 338, 6700 AH, Wageningen, The Netherlands. jeremie.vandenplas@wur.nl.

Genetics, Selection, Evolution : GSE
|June 27, 2019
PubMed
Summary
This summary is machine-generated.

A new diagonal preconditioner improves the convergence of iterative solvers for single-step single nucleotide polymorphism BLUP (ssSNPBLUP) models in animal breeding. This method is more computationally efficient than previous approaches, offering a practical solution for large datasets.

More Related Videos

One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
09:28

One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure

Published on: June 25, 2010

13.6K
Analysis of LINE-1 Retrotransposition at the Single Nucleus Level
11:52

Analysis of LINE-1 Retrotransposition at the Single Nucleus Level

Published on: April 23, 2016

8.8K

Related Experiment Videos

Last Updated: Jan 23, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs
12:08

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

19.5K
One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
09:28

One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure

Published on: June 25, 2010

13.6K
Analysis of LINE-1 Retrotransposition at the Single Nucleus Level
11:52

Analysis of LINE-1 Retrotransposition at the Single Nucleus Level

Published on: April 23, 2016

8.8K

Area of Science:

  • Animal Breeding and Genetics
  • Computational Biology
  • Numerical Analysis

Background:

  • The preconditioned conjugate gradient (PCG) method is widely used in animal breeding for solving linear systems.
  • PCG faces convergence challenges with single-step single nucleotide polymorphism BLUP (ssSNPBLUP) models.
  • The deflated PCG (DPCG) method addresses these issues but incurs significant computational costs.

Purpose of the Study:

  • To develop a cost-effective second-level preconditioner for ssSNPBLUP models.
  • To reduce the largest eigenvalues of the preconditioned coefficient matrix.
  • To compare the performance of the new preconditioner against existing (D)PCG methods.

Main Methods:

  • Proposed a second-level diagonal preconditioner based on the properties of the ssSNPBLUP preconditioned coefficient matrix.
  • Integrated the preconditioner with the standard (block-)diagonal preconditioner, avoiding extra computational expenses.
  • Evaluated the method on two distinct ssSNPBLUP models and datasets.

Main Results:

  • The second-level diagonal preconditioner effectively decreased the largest eigenvalues and condition number of the preconditioned matrices.
  • Observed improved convergence patterns for the iterative solver.
  • While slower in convergence for the largest dataset, the proposed method showed better overall computing time compared to DPCG.

Conclusions:

  • The proposed second-level diagonal preconditioner enhances the convergence of (D)PCG methods for ssSNPBLUP models.
  • The PCG method with the novel preconditioner appears more efficient than DPCG for ssSNPBLUP.
  • The optimal solver-model combination is likely dependent on the specific application and dataset.