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

An iterative algorithm for correcting sequencing errors in DNA coding regions

Y Xu1, R J Mural, E C Uberbacher

  • 1Computer Science and Mathematics Division, Oak Ridge National Laboratory, Tennessee 37831-6364, USA. ying@mars.epm.ornl.gov

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 1, 1996
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

Computational tools for protein modeling.

Current protein & peptide science·2002
Same author

ARTEMIS: a tool for displaying and annotating DNA sequence.

Briefings in bioinformatics·2001
Same author

The sequence of the human genome.

Science (New York, N.Y.)·2001
Same author

Sequence-structure specificity of a knowledge based energy function at the secondary structure level.

Bioinformatics (Oxford, England)·2000
Same author

Current status of computational gene finding: a perspective.

Methods in enzymology·1999
Same author

The Genome Channel: a browser to a uniform first-pass annotation of genomic DNA.

Trends in genetics : TIG·1999
Same journal

GMSA: A Graph Matching and Point Cloud Registration-Based Method for Spatial Transcriptomics Data Alignment.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Investigations on Multiple Protein Scaffold Filling.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised Learning.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

PPIGAN: Prediction of Protein-Protein Interactions Using Generative Adversarial Networks.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Deep Structure-Enhanced Cell Clustering Model for Single-Cell RNA Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology·2026
Same journal

Asymmetric Drug-Drug Interaction Prediction Based on Generative Adversarial Networks and Knowledge Graph.

Journal of computational biology : a journal of computational molecular cell biology·2026
See all related articles

This study introduces an improved algorithm for detecting and correcting insertion/deletion (indel) errors in DNA coding sequences. The new method enhances accuracy in identifying and fixing indels, restoring proper DNA translation frames.

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Insertion and deletion (indel) errors in DNA coding regions disrupt gene translation.
  • Existing indel detection methods often fail due to frame shifts.

Purpose of the Study:

  • To present a more effective algorithm for localizing and correcting indels in DNA coding regions.
  • To improve the accuracy of indel detection and correction compared to previous methods.

Main Methods:

  • The algorithm identifies indels by detecting shifts in preferred DNA translation frames.
  • It corrects indels by inserting or deleting DNA bases to restore a consistent frame.
  • An iterative approach is used for repeated localization and correction until no more indels are found.

Related Experiment Videos

Main Results:

  • The improved algorithm detects and corrects a higher number of indels.
  • The rate of introducing false indels was not worsened compared to prior work.
  • Restoration of consistent translation frames within coding regions was achieved.

Conclusions:

  • The enhanced algorithm offers a more effective solution for handling indel errors in DNA sequencing.
  • This method has significant implications for accurate gene analysis and protein translation studies.