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

Two notes on genome rearrangement.

Michal Ozery-Flato1, Ron Shamir

  • 1School of Computer Science, Tel Aviv University, Israel. ozery@post.tau.ac.il

Journal of Bioinformatics and Computational Biology
|August 4, 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

MAMMAL - Molecular Aligned Multi-Modal Architecture and Language for biomedical discovery.

npj drug discovery·2026
Same author

The Effect of Nephrology Referral on CKD Outcomes in Israel.

Clinical journal of the American Society of Nephrology : CJASN·2026
Same author

Demography-dependent variability in the human tumor mycobiome.

Microbiology spectrum·2026
Same author

Generation of Automated Nephrometry Scores Through Direct Prediction of Each Component.

Urology·2026
Same author

Optimizing Parkinson's disease progression scales using computational methods.

NPJ Parkinson's disease·2026
Same author

HLA export by melanoma cells decoys cytotoxic T cells to promote immune evasion.

Cell·2025
Same journal

CNV-ECOD: A copy number variation detection method based on ECOD algorithm using next-generation sequencing data.

Journal of bioinformatics and computational biology·2026
Same journal

ReinVar: A model-free paradigm-based reinforcement learning approach to detect copy number variation.

Journal of bioinformatics and computational biology·2026
Same journal

When pipelines run but coordinates fail: A simple spatial specificity check for false locality in post-GWAS analysis.

Journal of bioinformatics and computational biology·2026
Same journal

Comparative benchmarking of template-based, evolutionary-diffusion, and generative language models for IsPETase structure prediction.

Journal of bioinformatics and computational biology·2026
Same journal

Trap spaces as labelled ideals of SCC posets: A structural-functional theory of reachability in asynchronous boolean networks.

Journal of bioinformatics and computational biology·2026
Same journal

Designing of sorafenib analogs to target c-Raf for the management of hepatocellular carcinoma: Molecular dynamics and mmPBSA analysis.

Journal of bioinformatics and computational biology·2026
See all related articles

This study corrects a failure in the Hannenhalli-Pevzner theorem for sorting signed genomes by reversals and translocations (SBRT). It also establishes a quadratic lower bound for sorting signed permutations by reversals (SBR) algorithms.

Area of Science:

  • Computational Biology
  • Genomics
  • Bioinformatics

Background:

  • Genome rearrangement is a key problem in computational biology.
  • Sorting signed genomes by reversals and translocations (SBRT) is a significant challenge.
  • Existing algorithms for SBRT have limitations.

Purpose of the Study:

  • To address a specific failure in the Hannenhalli-Pevzner theorem for SBRT.
  • To propose a correction to the SBRT theorem and its associated polynomial algorithm.
  • To establish a lower bound for sorting signed permutations by reversals (SBR) algorithms.

Main Methods:

  • Analysis of the specific case where the Hannenhalli-Pevzner theorem fails.
  • Development of a corrected theorem and algorithm for SBRT.

Related Experiment Videos

  • Reduction of SBRT to SBR.
  • Graph-theoretic analysis using overlap and interleaving graphs for SBR.

    • Main Results:

    • Identification and description of the failure case in SBRT.
    • A corrected theorem and polynomial-time algorithm for SBRT.
    • A family of signed permutations demonstrating a quadratic lower bound for SBR algorithms.
    • An Omega(n3) lower bound for Bergeron's SBR algorithm.

    Conclusions:

    • The proposed correction resolves the identified failure in SBRT.
    • The established lower bound has implications for the efficiency of SBR algorithms.
    • This work advances the understanding and computational approaches to genome rearrangement problems.