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

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

403
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
403
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

16.4K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
16.4K
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

12.2K
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...
12.2K
Graphs of Equations in Two Variables01:30

Graphs of Equations in Two Variables

90
An equation with two variables, typically written in the form y = f(x) or Ax + By = C, describes a relationship between quantities represented by x and y. Each solution to such an equation is an ordered pair (x, y) that satisfies the equation when substituted. These pairs can be represented graphically to understand the variables' relationship visually.A common technique for constructing the graph of a two-variable equation is to create a value table. Begin by choosing several values for the...
90
Graphical Representation of Inequalities01:28

Graphical Representation of Inequalities

85
The graph of the equation where y equals x squared forms a curve known as a parabola. This curve acts as a boundary in the coordinate plane, dividing it into distinct regions based on the relative position of points.When the equality sign in the equation is replaced with an inequality—such as greater than, less than, greater than or equal to, or less than or equal to—the graphical representation changes from a single curve into a broader shaded area that signifies the set of all...
85
Ogive Graph01:07

Ogive Graph

6.4K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
6.4K

You might also read

Related Articles

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

Sort by
Same author

Population-scale Y chromosome assemblies reveal recurrent remodeling within constrained architectures.

bioRxiv : the preprint server for biology·2026
Same author

Complete genomes of a multi-generational pedigree to expand studies of genetic and epigenetic inheritance.

bioRxiv : the preprint server for biology·2025
Same author

Sequence-to-graph alignment based copy number calling using a network flow formulation.

bioRxiv : the preprint server for biology·2025
Same author

Locityper enables targeted genotyping of complex polymorphic genes.

Nature genetics·2025
Same author

A complete diploid human genome benchmark for personalized genomics.

bioRxiv : the preprint server for biology·2025
Same author

Author Correction: Complex genetic variation in nearly complete human genomes.

Nature·2025
Same journal

Integrated lipidomic and transcriptomic profiling of the host response in human malaria.

Genome biology·2026
Same journal

Centromeric satellite expansion drives genome evolution in the snowy owl.

Genome biology·2026
Same journal

Mapping the landscape of allele-specific expression in porcine genomes.

Genome biology·2026
Same journal

Genomic sequence evolution underlying human neocortical interareal diversification.

Genome biology·2026
Same journal

Regulatory mechanisms driven by functional 3'-UTR variants in alcohol use disorder and related traits.

Genome biology·2026
Same journal

A longitudinal single-nucleus transcriptomic atlas of bovine placentation reveals dynamic cellular hierarchies and regulatory programs.

Genome biology·2026
See all related articles

Related Experiment Video

Updated: Dec 7, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.8K

GraphAligner: rapid and versatile sequence-to-graph alignment.

Mikko Rautiainen1,2,3, Tobias Marschall4

  • 1Center for Bioinformatics, Saarland University, Saarland Informatics Campus E2.1, Saarbrücken, 66123, Germany. m_rautiainen@hotmail.com.

Genome Biology
|September 25, 2020
PubMed
Summary
This summary is machine-generated.

GraphAligner significantly accelerates sequence alignment to genome graphs, improving speed and reducing memory usage for genomic analysis. This tool enhances accuracy and efficiency in applications like error correction and genome assembly.

Keywords:
Error correctionGenome graphsLong readsPangenomeSequence alignment

More Related Videos

A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.9K
Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

7.3K

Related Experiment Videos

Last Updated: Dec 7, 2025

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
10:40

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

10.8K
A Practical Guide to Phylogenetics for Nonexperts
12:00

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

35.9K
Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group
07:49

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

7.3K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Genome graphs are essential for representing genetic variation and sequence uncertainty.
  • Aligning sequences to genome graphs is crucial for pangenomics, error correction, and genome assembly.
  • Current alignment methods are often computationally intensive and slow.

Purpose of the Study:

  • To introduce GraphAligner, a novel tool for efficient long-read alignment to genome graphs.
  • To evaluate the performance of GraphAligner against existing state-of-the-art tools.

Main Methods:

  • Development of GraphAligner, a tool optimized for aligning long sequencing reads to genome graphs.
  • Benchmarking GraphAligner's speed and memory usage against established alignment tools.
  • Assessing GraphAligner's performance in read error correction applications.

Main Results:

  • GraphAligner achieves 13x greater speed and uses 3x less memory compared to current tools.
  • In error correction tasks, GraphAligner demonstrates over twice the accuracy and is more than 12x faster than existing methods.

Conclusions:

  • GraphAligner offers a substantial improvement in performance for aligning sequences to genome graphs.
  • The tool's efficiency and accuracy make it valuable for various genomic applications, including pangenomics and error correction.