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

GRIMM: genome rearrangements web server.

Glenn Tesler1

  • 1Department of Computer Science and Engineering, University of California, San Diego, CA 92093-0114, USA.

Bioinformatics (Oxford, England)
|April 6, 2002
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

Correction: Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele.

PLoS genetics·2016
Same author

Predicting Carriers of Ongoing Selective Sweeps without Knowledge of the Favored Allele.

PLoS genetics·2015
Same author

Assembling single-cell genomes and mini-metagenomes from chimeric MDA products.

Journal of computational biology : a journal of computational molecular cell biology·2013
Same author

Candidate phylum TM6 genome recovered from a hospital sink biofilm provides genomic insights into this uncultivated phylum.

Proceedings of the National Academy of Sciences of the United States of America·2013
Same author

Genome of the pathogen Porphyromonas gingivalis recovered from a biofilm in a hospital sink using a high-throughput single-cell genomics platform.

Genome research·2013
Same author

Characterizing the relationship between steady state and response using analytical expressions for the steady states of mass action models.

PLoS computational biology·2013

Genome Rearrangements In Man and Mouse (GRIMM) is a novel bioinformatics tool for analyzing gene order rearrangements in both single and multiple chromosomes. It offers a new algorithm for comparative genomic mapping, even when gene directions are unknown.

Area of Science:

  • Comparative genomics
  • Bioinformatics tools
  • Computational biology

Background:

  • Analyzing gene order rearrangements is crucial for understanding genome evolution.
  • Existing tools primarily focus on unichromosomal genomes.
  • Comparative mapping with unknown gene directions presents a significant challenge.

Purpose of the Study:

  • To introduce Genome Rearrangements In Man and Mouse (GRIMM), a new software tool.
  • To enable the analysis of gene order rearrangements in multichromosomal genomes.
  • To provide a novel algorithm for comparative mapping with unsigned gene data.

Main Methods:

  • Development of the GRIMM software tool.
  • Implementation of algorithms for analyzing gene order rearrangements.

Related Experiment Videos

  • Application to both unichromosomal and multichromosomal genomes.
  • Inclusion of methods for handling signed and unsigned gene data.
  • Main Results:

    • GRIMM successfully analyzes gene order rearrangements in multichromosomal genomes.
    • The tool accommodates both signed and unsigned gene data.
    • A new algorithm is presented for comparative maps with unknown gene directions.

    Conclusions:

    • GRIMM is the first tool capable of analyzing rearrangements in multichromosomal genomes.
    • GRIMM offers a comprehensive solution for comparative genomic analysis.
    • The tool enhances the study of genome evolution and structural variations.