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 Experiment Videos

A nearest-neighboring-end algorithm for genetic mapping.

Charles F Crane1, Yan M Crane

  • 1USDA-ARS and Department of Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907, USA. ccrane@purdue.edu

Bioinformatics (Oxford, England)
|November 27, 2004
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Tar spot susceptibility of corn influences phyllosphere-associated bacterial and fungal microbiomes.

Frontiers in microbiology·2025
Same author

Biotype and host relatedness influence the composition of bacterial microbiomes in <i>Schizaphis graminum</i> aphids.

Frontiers in microbiology·2025
Same author

Shotgun Metagenome Analysis of Two <i>Schizaphis graminum</i> Biotypes over Time With and Without Carried Cereal Yellow Dwarf Virus.

Insects·2025
Same author

Differential gene expression between viruliferous and non-viruliferous Schizaphis graminum (Rondani).

PloS one·2023
Same author

Molecular characterization of eliminated chromosomes in Hessian fly (Mayetiola destructor (Say)).

Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology·2023
Same author

slag: A program for seeded local assembly of genes in complex genomes.

Molecular ecology resources·2022
Same journal

Probabilistic RNA designability via interpretable ensemble approximation and dynamic decomposition.

Bioinformatics (Oxford, England)·2026
Same journal

Quantifying domain-specific relevance of computational biology Wikipedia articles using TF-IDF and cosine similarity.

Bioinformatics (Oxford, England)·2026
Same journal

GATSBI: improving context-aware protein embeddings through biologically motivated data splits.

Bioinformatics (Oxford, England)·2026
Same journal

BiMba: using Vision Mamba to predict protein sites that bind other proteins.

Bioinformatics (Oxford, England)·2026
Same journal

ProMeta: a meta-learning framework for robust disease diagnosis and prediction from plasma proteomics.

Bioinformatics (Oxford, England)·2026
Same journal

Is a Win-Win possible? Achieving pareto-optimal privacy-utility balance in fine-tuned genome language model embeddings against embedding reconstruction attacks.

Bioinformatics (Oxford, England)·2026
See all related articles

A new algorithm based on Kruskal's minimum spanning tree efficiently maps genetic markers in large populations. It improves local marker order but struggles with gaps in linkage groups.

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput genotyping enables associating phenotypes with candidate loci.
  • Current mapping algorithms require hierarchical maps for large datasets.

Purpose of the Study:

  • To develop and evaluate a novel algorithm for genetic mapping using a minimum spanning tree approach.
  • To assess the algorithm's performance across various population types and data conditions.

Main Methods:

  • Adapted Kruskal's minimum spanning tree algorithm for genetic marker deletion from linkage groups.
  • Algorithm progressively joins groups and corrects erroneous joins based on recombination fractions.
  • Evaluated performance through simulations and application to bread wheat (Triticum aestivum) mapping.

Related Experiment Videos

Main Results:

  • Algorithm efficiently handles large datasets (up to 37,005 markers) and various population types.
  • Successfully recovered true map order in simulations under uniform marker distribution.
  • Shortened an existing bread wheat map by 16% but failed to bridge gaps within linkage groups.

Conclusions:

  • The algorithm is effective for improving local marker ordering within linkage groups.
  • Susceptible to sampling, typing errors, and joint selection affecting terminal markers.
  • Further development needed to address challenges with gaps and improve global map assembly.