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

12.1K
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...
12.1K
Block Diagram Reduction01:22

Block Diagram Reduction

202
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
202
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

228
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
228
Theorems of Pappus and Guldinus: Problem Solving01:12

Theorems of Pappus and Guldinus: Problem Solving

732
Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a...
732
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

226
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
226
SFG Algebra01:16

SFG Algebra

116
In Signal Flow Graph (SFG) algebra, the value a node represents is determined by the sum of all signals entering that node. This summed value is then transmitted through every branch leaving the node, making the SFG a powerful tool for visualizing and analyzing control systems.
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...
116

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

EGGS: Empirical Genotype Generalizer for Samples.

Bioinformatics advances·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 journal

Haplotype-aware long-read error correction.

Algorithms for molecular biology : AMB·2026
Same journal

Extension of partial atom-to-atom maps: uniqueness and algorithms.

Algorithms for molecular biology : AMB·2026
Same journal

Lossless pangenome indexing using tag arrays.

Algorithms for molecular biology : AMB·2026
Same journal

Dolphyin: a combinatorial algorithm for identifying 1-Dollo phylogenies in cancer.

Algorithms for molecular biology : AMB·2026
Same journal

Probing transcription factor subsets in gene regulatory networks.

Algorithms for molecular biology : AMB·2026
Same journal

Comparing the ability of embedding methods on metabolic hypergraphs for capturing taxonomy-based features.

Algorithms for molecular biology : AMB·2026
See all related articles

Related Experiment Video

Updated: Jun 25, 2025

Protocols for C-Brick DNA Standard Assembly Using Cpf1
12:03

Protocols for C-Brick DNA Standard Assembly Using Cpf1

Published on: June 15, 2017

8.3K

Compression algorithm for colored de Bruijn graphs.

Amatur Rahman1, Yoann Dufresne2,3, Paul Medvedev4,5,6

  • 1Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA. amatur003@gmail.com.

Algorithms for Molecular Biology : AMB
|May 26, 2024
PubMed
Summary
This summary is machine-generated.

We developed ESS-color, a new tool for compressing colored de Bruijn graphs (sets of k-mers with assigned colors) for disk storage. ESS-color significantly reduces file sizes, improving scalability for bioinformatics applications like genome assembly.

More Related Videos

Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

15.0K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.4K

Related Experiment Videos

Last Updated: Jun 25, 2025

Protocols for C-Brick DNA Standard Assembly Using Cpf1
12:03

Protocols for C-Brick DNA Standard Assembly Using Cpf1

Published on: June 15, 2017

8.3K
Revealing Neural Circuit Topography in Multi-Color
09:11

Revealing Neural Circuit Topography in Multi-Color

Published on: November 14, 2011

15.0K
ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
05:12

ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data

Published on: January 16, 2019

11.4K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Data Compression

Background:

  • Colored de Bruijn graphs are crucial for genomics tasks like variant calling and genome assembly.
  • The large size of these graphs presents scalability challenges for researchers and developers.
  • Existing indexing structures focus on fast queries, neglecting space-efficient disk compression.

Purpose of the Study:

  • To develop a specialized tool for compressing colored de Bruijn graphs to disk.
  • To address the lack of efficient disk compression methods for these data structures.
  • To improve scalability and reproducibility in genomics data analysis.

Main Methods:

  • Developed a novel compression tool, ESS-color, building on prior work in k-mer set compression and graph indexing.
  • Implemented disk compression algorithms tailored for colored de Bruijn graphs.
  • Evaluated ESS-color's performance on diverse datasets, including sequencing data and whole genomes.

Main Results:

  • ESS-color achieved superior compression ratios across all tested datasets compared to existing methods.
  • The tool consistently outperformed other evaluated compression tools.
  • No other tool could achieve less than a 44% space overhead, highlighting ESS-color's efficiency.

Conclusions:

  • ESS-color offers a significant advancement in compressing colored de Bruijn graphs for disk storage.
  • The tool enhances scalability and aids reproducibility in bioinformatics.
  • The software is publicly available, encouraging wider adoption and development.