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

Next-generation Sequencing03:00

Next-generation Sequencing

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.
RNA-seq03:21

RNA-seq

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 microarray-based...
Sanger Sequencing01:57

Sanger Sequencing

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...
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

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...
Genome Annotation and Assembly03:36

Genome Annotation and Assembly

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.
Multi-species Conserved Sequences02:51

Multi-species Conserved Sequences

Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale  studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved DNA...

You might also read

Related Articles

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

Sort by
Same author

Long-Term Outcomes of Glucagon-Like Peptide-1 Receptor Agonists in Patients With Peripheral Artery Disease and Type 2 Diabetes.

Journal of the American Heart Association·2026
Same author

AI-enhanced ECG for acute coronary syndrome triage: A state-of-the-art review.

Cardiovascular revascularization medicine : including molecular interventions·2026
Same author

Diagnostic Approach to Left Ventricular Hypertrophy: A Review.

US cardiology·2026
Same author

REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis.

IEEE transactions on medical imaging·2026
Same author

Outcomes of TAVR Plus TEVAR Versus TAVR Alone in Patients with Concomitant Aortic Stenosis and Thoracic Aortic Aneurysm.

Heart, lung & circulation·2026
Same author

Transcatheter Tricuspid Valve Intervention Versus Optimal Medical Therapy in Symptomatic Tricuspid Regurgitation: A Systematic Review and Meta-Analysis of Randomized and Observational Studies.

The American journal of cardiology·2026
Same journal

Cross-Domain Transfer Learning from Peptides to Metabolites Using a Multi-Property Fine-Tuned LLM.

Bioinformatics (Oxford, England)·2026
Same journal

Biomedical Concept Recognition with Error-aware Negative-enhanced Ranking Framework.

Bioinformatics (Oxford, England)·2026
Same journal

TEDLH: Domain HMMs for sensitive detection of remote homologues.

Bioinformatics (Oxford, England)·2026
Same journal

PLNFGL: Joint Estimation of Multi-Condition Gene Networks from Single-cell RNA-seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

MCFST: Spatial domain identification method based on multi-view graph convolutional network and graph fusion network.

Bioinformatics (Oxford, England)·2026
Same journal

SpaBiT: Enhancing Spatial Transcriptomics Resolution via Bidirectional Attention Transformers.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Jun 6, 2026

Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Anatomy of a hash-based long read sequence mapping algorithm for next generation DNA sequencing.

Sanchit Misra1, Ankit Agrawal, Wei-keng Liao

  • 1Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA. smi539@eecs.northwestern.edu

Bioinformatics (Oxford, England)
|November 20, 2010
PubMed
Summary
This summary is machine-generated.

AGILE is a new algorithm for mapping long DNA sequencing reads to reference genomes. It is significantly faster than existing tools like BLAT and SSAHA2 for common error rates and read lengths, aiding in personalized medicine applications.

More Related Videos

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

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

Related Experiment Videos

Last Updated: Jun 6, 2026

Collection and Extraction of Saliva DNA for Next Generation Sequencing
06:58

Collection and Extraction of Saliva DNA for Next Generation Sequencing

Published on: August 27, 2014

Targeted DNA Methylation Analysis by Next-generation Sequencing
08:38

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

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

Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Short-read mapping tools are inefficient for longer DNA sequences (>200 bp).
  • Next-generation sequencing generates increasingly longer reads.
  • Efficient long-read mapping is crucial for resequencing and personalized medicine.

Purpose of the Study:

  • To develop a high-throughput algorithm for mapping long sequencing reads.
  • To improve the speed and accuracy of long-read sequence alignment.

Main Methods:

  • Developed AGILE (AliGnIng Long rEads), a hash table-based algorithm.
  • Utilized diagonal multiple seed-match criteria and q-gram filtering.
  • Implemented a dynamic incremental search approach for optimization.

Main Results:

  • AGILE demonstrated accuracy comparable to BWA-SW and SSAHA2, and higher than BLAT.
  • AGILE is significantly faster than BLAT, SSAHA2, and BWA-SW for practical error rates (<5%) and read lengths (200-1000 bp).

Conclusions:

  • AGILE offers a faster and accurate solution for long-read sequence mapping.
  • The algorithm is well-suited for applications like SNP identification and rare transcript detection in personalized medicine.