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

19.3K
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.
19.3K
RNA-seq03:21

RNA-seq

10.3K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.3K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

11.4K
In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...
11.4K
Genomics02:02

Genomics

37.3K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
37.3K
Next-generation Sequencing03:00

Next-generation Sequencing

92.4K
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....
92.4K
Sanger Sequencing01:57

Sanger Sequencing

756.5K
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...
756.5K

You might also read

Related Articles

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

Sort by
Same author

GHF-ACL: A novel contrastive learning framework with multi-order graph structures for herb-disease association prediction.

PLoS computational biology·2026
Same author

CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images.

Briefings in bioinformatics·2026
Same author

TCRBinder: Unified pre-trained language model with paired-chain synergy for predicting T-cell receptor binding specificity.

PLoS computational biology·2026
Same author

GMHAN: a heterogeneous graph attention framework for prioritizing coding and non-coding driver genes.

Bioinformatics (Oxford, England)·2026
Same author

SINTER3D: continuous 3D reconstruction of spatial transcriptomics via implicit neural representations.

Genome biology·2026
Same author

spAttClu: a spatial domain clustering model leveraging spatially weighted graph attention and contrastive learning.

Bioinformatics (Oxford, England)·2026
Same journal

STED: flexible cross-modal topic modeling infers cell-type-specific regulatory landscapes from bulk epigenomics.

Briefings in bioinformatics·2026
Same journal

A knowledge-guided deep learning framework for quantitative nucleic acid testing.

Briefings in bioinformatics·2026
Same journal

Optimal transport for label transfer in single-cell multi-omics integration.

Briefings in bioinformatics·2026
Same journal

Continuous multi-omics pathway enrichment analysis resolves hidden functional heterogeneity.

Briefings in bioinformatics·2026
Same journal

Evaluating completeness, coherence, and consistency of genome-scale function annotations.

Briefings in bioinformatics·2026
Same journal

Transformers for single-cell RNA sequencing: a survey.

Briefings in bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Sep 2, 2025

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

5.2K

Complex genome assembly based on long-read sequencing.

Tianjiao Zhang1, Jie Zhou1, Wentao Gao1

  • 1College of Information and Computer Engineering, Northeast Forestry University, Harbin, 150040, China.

Briefings in Bioinformatics
|August 8, 2022
PubMed
Summary
This summary is machine-generated.

Long-read sequencing advances complex genome assembly, enabling complete and haplotype-resolved genomes. Uncollapsed assembly, the most accurate method, integrates genome assembly and haplotype reconstruction for future routine use.

Keywords:
genome assemblyhaplotypelong-read sequencing

More Related Videos

Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

23.0K
Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

8.7K

Related Experiment Videos

Last Updated: Sep 2, 2025

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

5.2K
Ultra-long Read Sequencing for Whole Genomic DNA Analysis
10:34

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

23.0K
Novel Sequence Discovery by Subtractive Genomics
09:40

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

8.7K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-quality genome sequences are crucial for downstream genomic analyses.
  • Short-read sequencing struggles with complex genomes (high duplication, heterozygosity).
  • Long-read sequencing significantly enhances complex genome assembly integrity.

Purpose of the Study:

  • To review computational methods for complex genome assembly.
  • To detail theories, innovations, and limitations of long-read assemblers (collapsed, semi-collapsed, uncollapsed).
  • To highlight the relationship between genome assembly and haplotype reconstruction.

Main Methods:

  • Review of existing computational assembly methods.
  • Analysis of long-read sequencing assemblers.
  • Comparative assessment of collapsed, semi-collapsed, and uncollapsed assembly strategies.

Main Results:

  • Uncollapsed assembly is identified as the most accurate and complete genome representation.
  • Uncollapsed assembly intrinsically achieves haplotype reconstruction.
  • Haplotype reconstruction actively supports and improves uncollapsed assembly.

Conclusions:

  • Uncollapsed assembly represents the most effective strategy for complex genomes.
  • The synergy between genome assembly and haplotype reconstruction is critical.
  • Future research aims for routine, simple, and accurate complex genome assembly.