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

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

21.3K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
21.3K
Protein Complex Assembly02:41

Protein Complex Assembly

2.6K
2.6K
Protein Complex Assembly02:41

Protein Complex Assembly

17.0K
Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
17.0K
Oligosaccharide Assembly01:24

Oligosaccharide Assembly

3.8K
Protein glycosylation starts in the ER lumen and continues in the Golgi apparatus. Glycosyltransferases catalyze the addition of sugar molecules or glycosylation of proteins. Usually, these enzymes add sugars to the hydroxyl groups of selected serine or threonine residues to form O-linked glycans or the amino groups of asparagine residues to form N-linked glycans. Different positions on the same polypeptide chain can contain differently linked glycans.
Multiple sugar molecules that may or may...
3.8K
Next-generation Sequencing03:00

Next-generation Sequencing

100.4K
The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....
100.4K
Sanger Sequencing01:57

Sanger Sequencing

777.2K
DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
777.2K

You might also read

Related Articles

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

Sort by
Same author

EMERALD-UI: an interactive web application to unveil novel protein biology hidden in the alternative alignment space.

Bioinformatics (Oxford, England)·2026
Same author

Hash functions in nucleotide sequence analysis.

Genome research·2026
Same author

Estimation of substitution and indel rates via <i>k</i>-mer statistics.

Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop)·2026
Same author

A k-mer-Based Estimator of the Substitution Rate Between Repetitive Sequences.

Algorithms in bioinformatics : ... International Workshop, WABI ..., proceedings. WABI (Workshop)·2026
Same author

Efficiency of Learned Indexes on Genome Spectra.

LIPIcs : Leibniz international proceedings in informatics·2026
Same author

The gift of novelty: repeat-robust <i>k</i>-mer-based estimators of mutation rates.

bioRxiv : the preprint server for biology·2026
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

Related Experiment Video

Updated: Mar 13, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

5.9K

Safe and Complete Contig Assembly Through Omnitigs.

Alexandru I Tomescu1, Paul Medvedev2,3,4

  • 11 Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki , Helsinki, Finland .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|October 18, 2016
PubMed
Summary
This summary is machine-generated.

Researchers introduce omnitigs, a new type of DNA sequence string derived from genome graphs. Omnitigs are significantly longer than traditional unitigs and offer improved representation of genomic variations.

Keywords:
contig assemblygenome assemblygraph algorithmomnitigsafe and complete algorithm

More Related Videos

Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

9.2K
Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example
05:45

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

9.4K

Related Experiment Videos

Last Updated: Mar 13, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies
12:08

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

5.9K
Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

9.2K
Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example
05:45

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

9.4K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome assembly is crucial for reconstructing genomes from sequencing reads.
  • Current contig assembly methods aim for longer contiguous sequences but face limitations.
  • Identifying all safely reportable strings from genome graphs remains an open challenge.

Purpose of the Study:

  • To define and identify all strings that can be safely reported as contigs from a genome graph.
  • To introduce a novel class of sequences called omnitigs.
  • To develop an efficient algorithm for finding omnitigs.

Main Methods:

  • Modeling the genome as a circular covering walk.
  • Developing a polynomial-time algorithm to identify omnitigs from genome graphs.
  • Comparing the length and properties of omnitigs against existing unitigs using experimental data.

Main Results:

  • Omnitigs represent a comprehensive set of strings derivable from genome graphs.
  • The proposed algorithm efficiently finds omnitigs in polynomial time.
  • Omnitigs are 66%-82% longer on average than unitigs.
  • Omnitigs show increased neighborhood representation for 29% of dbSNP locations compared to unitigs.

Conclusions:

  • Omnitigs provide a more complete and longer representation of genomic sequences compared to unitigs.
  • The developed algorithm offers an efficient method for discovering omnitigs.
  • Omnitigs have the potential to improve genome assembly accuracy and variant detection.