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 Concept Videos

Mismatch Repair01:36

Mismatch Repair

Overview
Mismatch Repair01:20

Mismatch Repair

Organisms are capable of detecting and fixing nucleotide mismatches that occur during DNA replication. This sophisticated process requires identifying the new strand and replacing the erroneous bases with correct nucleotides. Mismatch repair is coordinated by many proteins in both prokaryotes and eukaryotes.
The Mutator Protein Family Plays a Key Role in DNA Mismatch Repair
The human genome has more than 3 billion base pairs of DNA per cell. Prior to cell division, that vast amount of genetic...
Mismatch Repair01:36

Mismatch Repair

Overview
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.
Long-patch Base Excision Repair01:02

Long-patch Base Excision Repair

Since the discovery of the two BER pathways, there has been a debate about how a cell chooses one pathway over the other and the factors determining this selection. Numerous in vitro experiments have pointed out multiple determinants for the sub-pathway selection. These are:
Improving Translational Accuracy02:07

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

You might also read

Related Articles

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

Sort by
Same author

Disambiguating a Soft Metagenomic Clustering.

Journal of computational biology : a journal of computational molecular cell biology·2025
Same author

SCEMENT: scalable and memory efficient integration of large-scale single-cell RNA-sequencing data.

Bioinformatics (Oxford, England)·2025
Same author

p65 signaling dynamics drive the developmental progression of hematopoietic stem and progenitor cells through cell cycle regulation.

Nature communications·2024
Same author

GraphSlimmer: Preserving Read Mappability with the Minimum Number of Variants.

Journal of computational biology : a journal of computational molecular cell biology·2024
Same author

Dynamic relationships among pathways producing hydrocarbons and fatty acids of maize silk cuticular waxes.

Plant physiology·2024
Same author

Nod1-dependent NF-kB activation initiates hematopoietic stem cell specification in response to small Rho GTPases.

Nature communications·2023
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Jun 4, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Repeat-aware modeling and correction of short read errors.

Xiao Yang1, Srinivas Aluru, Karin S Dorman

  • 1Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa 50011, USA. xyang@iastate.edu

BMC Bioinformatics
|February 24, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistical method for accurate error detection and correction in high-throughput sequencing data, especially for genomes with repetitive sequences.

More Related Videos

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Related Experiment Videos

Last Updated: Jun 4, 2026

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
09:30

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms

Published on: September 13, 2018

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput short read sequencing is vital for genomics and systems biology.
  • Accurate error detection and correction are critical for applications like de novo genome sequencing.
  • Existing methods struggle with genomes containing high repeat content.

Purpose of the Study:

  • To develop a statistical model and computational method for robust error detection and correction.
  • To address the challenges posed by genomic repeats in short read sequencing.
  • To improve the accuracy of error correction in complex genomes.

Main Methods:

  • Developed a statistical model to infer true genomic kmer frequencies from observed frequencies.
  • Proposed a method to analyze misread relationships among kmers.
  • Created a threshold estimation method for kmer validation.
  • Modeled position-dependent error occurrence frequencies.

Main Results:

  • Achieved superior error detection compared to existing methods.
  • Demonstrated improved error correction, particularly for genomes with high repeat content.
  • Successfully modeled non-uniform error distributions within sequencing reads.

Conclusions:

  • Introduced a novel statistical framework for modeling sequencing errors in next-generation reads.
  • The framework shows significant promise for detecting and correcting errors in repetitive genomes.
  • This work advances the accuracy of genomic data analysis for complex biological systems.