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

Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.2K
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...
12.2K
Bewley Lattice Diagram01:12

Bewley Lattice Diagram

708
The Bewley lattice diagram, developed by L. V. Bewley, effectively organizes the reflections occurring during transmission-line transients. It visually represents how voltage waves propagate and reflect within a transmission line, making it easier to understand the complex interactions that occur.
708
pV-Diagrams01:18

pV-Diagrams

4.2K
The pV diagram, which is a graph of pressure versus volume of the gas under study, is helpful in describing certain aspects of the substance. When the substance behaves like an ideal gas, the ideal gas equation describes the relationship between its pressure and volume. On a pV diagram, it is common to plot an isotherm, which is a curve showing p as a function of V with the number of molecules and the temperature fixed. Then, for an ideal gas, the product of the pressure of the gas and its...
4.2K
Multiple Bar Graph01:07

Multiple Bar Graph

5.3K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
5.3K
Ogive Graph01:07

Ogive Graph

5.7K
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...
5.7K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

3.1K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.1K

You might also read

Related Articles

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

Sort by
Same author

Kaminari: a frugal colored index for approximate <i>k</i>-mer queries.

Bioinformatics advances·2026
Same author

Highly Constrained Kinetic Models for Single-Cell Gene Expression Analysis.

bioRxiv : the preprint server for biology·2026
Same author

Surgical Management and Outcomes of Large High Myopic Macular Holes: Global Macular Hole Multicenter Study 3.

Retina (Philadelphia, Pa.)·2026
Same author

Complex Retinal Detachment in an Adult Patient With Familial Exudative Vitreoretinopathy: Challenges in Diagnosis and Management.

Journal of vitreoretinal diseases·2026
Same author

<i>k</i> ache-hash: A dynamic, concurrent, and cache-efficient hash table for streaming <i>k</i> -mer operations.

bioRxiv : the preprint server for biology·2026
Same author

Optimizing sparse and skew hashing: faster <math><mi>k</mi></math> -mer dictionaries.

bioRxiv : the preprint server for biology·2026
Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026
Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026
Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026
Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026
Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026
Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026
See all related articles

Related Experiment Video

Updated: Jul 19, 2025

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
07:05

Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

Published on: June 18, 2021

2.5K

Meta-colored compacted de Bruijn graphs.

Giulio Ermanno Pibiri, Jason Fan, Rob Patro

    Biorxiv : the Preprint Server for Biology
    |August 7, 2023
    PubMed
    Summary
    This summary is machine-generated.

    A new meta-colored compacted de Bruijn graph (Mac-dBG) significantly reduces memory usage for large genomic datasets. This data structure improves compression and query efficiency for pangenomics applications.

    More Related Videos

    Revealing Neural Circuit Topography in Multi-Color
    09:11

    Revealing Neural Circuit Topography in Multi-Color

    Published on: November 14, 2011

    15.1K
    Generating Strictly Controlled Stimuli for Figure Recognition Experiments
    05:39

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments

    Published on: March 18, 2019

    5.3K

    Related Experiment Videos

    Last Updated: Jul 19, 2025

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
    07:05

    Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters

    Published on: June 18, 2021

    2.5K
    Revealing Neural Circuit Topography in Multi-Color
    09:11

    Revealing Neural Circuit Topography in Multi-Color

    Published on: November 14, 2011

    15.1K
    Generating Strictly Controlled Stimuli for Figure Recognition Experiments
    05:39

    Generating Strictly Controlled Stimuli for Figure Recognition Experiments

    Published on: March 18, 2019

    5.3K

    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • The colored compacted de Bruijn graph (c-dBG) is crucial for genomics tasks like read mapping and abundance estimation.
    • Efficiently retrieving k-mer colors (references) from c-dBGs is vital but memory-intensive for large datasets.
    • Reducing the memory footprint of c-dBG color storage is essential for scalable sequence indexing.

    Approach:

    • Introduced the meta-colored compacted de Bruijn graph (Mac-dBG) data structure.
    • Represented colors holistically, factoring and compressing common sub-patterns across the entire indexed collection.
    • Developed a heuristic algorithm to optimize space, acknowledging the NP-hard nature of the problem.

    Key Points:

    • Mac-dBG achieves superior compression effectiveness compared to previous methods.
    • Maintained or improved query efficiency alongside significant space reduction.
    • Demonstrated robust performance across diverse datasets and query workloads.

    Conclusions:

    • Mac-dBG offers a substantially improved space/time trade-off for large-scale sequence indexing.
    • The holistic color representation is key to its enhanced compression capabilities.
    • Provides a practical and efficient solution for pangenomic data analysis.