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

On the complexity of sparse exon assembly.

Carmel Kent1, Gad M Landau, Michal Ziv-Ukelson

  • 1Department of Computer Science, University of Haifa, Haifa Israel. ckent@cs.haifa.ac.il

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|June 27, 2006
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

New algorithms for structure informed genome rearrangement.

Algorithms for molecular biology : AMB·2023
Same author

Predicting the pathogenicity of bacterial genomes using widely spread protein families.

BMC bioinformatics·2022
Same author

Approximate search for known gene clusters in new genomes using PQ-trees.

Algorithms for molecular biology : AMB·2021
Same author

Discovery of multi-operon colinear syntenic blocks in microbial genomes.

Bioinformatics (Oxford, England)·2020
Same author

A New Paradigm for Identifying Reconciliation-Scenario Altering Mutations Conferring Environmental Adaptation.

Journal of computational biology : a journal of computational molecular cell biology·2020
Same author

Student engagement and wellbeing over time at a higher education institution.

PloS one·2019

This study presents a novel combinatorial method for the Exon Assembly Problem in computational molecular biology. The approach efficiently reconstructs gene structures from candidate exon blocks using sequence similarity.

Area of Science:

  • Computational Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Gene structure prediction is crucial for understanding gene function and regulation.
  • Existing methods often face challenges in accurately assembling gene components from fragmented evidence.
  • The Exon Assembly Problem, a key step in gene prediction, requires efficient algorithms for interpreting evidence.

Purpose of the Study:

  • To develop a combinatorial solution for the Exon Assembly Problem.
  • To propose a similarity-based approach for reconstructing gene structures.
  • To address the sparse data scenario with a limited number of candidate exon blocks.

Main Methods:

  • A combinatorial algorithm is proposed to solve the Exon Assembly Problem.
  • The method utilizes a similarity-based strategy, comparing candidate exons to a homologous sequence.

Related Experiment Videos

  • The algorithm is designed for sparse datasets, considering O(n) candidate exon blocks.

    • Main Results:

    • The developed algorithm provides an efficient solution to the Exon Assembly Problem.
    • The approach yields a time complexity of O(n^2 * sqrt(n)) for assembling gene structures.
    • Demonstrates feasibility in reconstructing gene architecture from filtered exon data.

    Conclusions:

    • The proposed combinatorial method offers an effective solution for gene structure prediction.
    • This similarity-based approach enhances the interpretation of evidence in computational biology.
    • The algorithm's efficiency makes it suitable for analyzing sparse genomic datasets.