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

Euler's Formula to Columns: Problem Solving01:23

Euler's Formula to Columns: Problem Solving

1.1K
Euler's formula is used in structural engineering to determine the buckling load of columns under various conditions. However, when dealing with systems that incorporate both rigid elements and elastic components, such as springs, the analysis requires a finer approach to determine the critical load. The problem described involves two rigid bars connected at a pivot point with a spring attached and a vertical load applied at one end.
The system comprises two vertical rigid bars, AB and BC, of...
1.1K
Trigonometric Substitution01:23

Trigonometric Substitution

132
Trigonometric substitution is a technique used to simplify integrals that contain square root expressions involving quadratic forms. It is particularly effective when the integrand includes terms resembling those found in standard geometric equations, such as circles or ellipses.Molniya satellites follow highly elliptical orbits, repeatedly sweeping out the same regions of space as they revolve around Earth. To estimate the area enclosed by such an orbit, the path is modeled as an ellipse...
132
Euler's Formula to Columns with Other End Conditions01:15

Euler's Formula to Columns with Other End Conditions

1.2K
Euler's formula is very important in the field of structural engineering, providing a foundation for understanding the critical loading conditions of pin-ended columns. This formula links the modulus of elasticity, the moment of inertia of the cross-section, and the column's length, offering a precise calculation of the critical load at which a column is prone to buckling.
1.2K
The Binomial Theorem01:30

The Binomial Theorem

446
The Binomial Theorem is a foundational principle in algebra used to expand expressions raised to a power. It provides a structured approach for expanding binomials of the form (a+b)n, where a and b are variables or constants representing algebraic expressions, and n is a non-negative integer.The general form of the Binomial Theorem is:Each term in the expansion involves a binomial coefficient, which is calculated using factorials:The exponent of a in each term decreases from n to 0, while the...
446
Euler Equations of Motion01:19

Euler Equations of Motion

697
Imagine a rigid body that is rotating at an angular velocity of ω within an inertial frame of reference. Along with this, picture a second rotating frame that is attached to the body itself. This frame moves along with the body and possesses an angular velocity of Ω. The total moment about the center of mass is calculated by adding the rate of change of angular momentum about the center of mass in relation to the rotating frame and the cross-product of the body's angular velocity...
697
Atomic Orbitals02:44

Atomic Orbitals

47.2K
An atomic orbital represents the three-dimensional regions in an atom where an electron has the highest probability to reside. The radial distribution function indicates the total probability of finding an electron within the thin shell at a distance r from the nucleus. The atomic orbitals have distinct shapes which are determined by l, the angular momentum quantum number. The orbitals are often drawn with a boundary surface, enclosing densest regions of the cloud.
47.2K

You might also read

Related Articles

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

Sort by
Same author

Circulating causal protein networks linked to future risk of myocardial infarction.

Nature communications·2025
Same author

Generating random graphs with prescribed graphlet frequency bounds derived from probabilistic networks.

PloS one·2025
Same author

Mechanistic Insights into Tumorigenesis from Serum Proteins.

medRxiv : the preprint server for health sciences·2025
Same author

Plasma proteins are integral to gene-regulatory networks acting within and across blood cells, the arterial wall and major metabolic organs.

medRxiv : the preprint server for health sciences·2025
Same author

Circulating causal protein networks linked to future risk of myocardial infarction.

medRxiv : the preprint server for health sciences·2025
Same author

A Network-Driven Framework for Enhancing Gene-Disease Association Studies in Coronary Artery Disease.

ArXiv·2025
Same journal

Invaders taking over-Mollusc faunal change in volcanic barrier lakes of the Albertine Rift biodiversity hotspot.

PloS one·2026
Same journal

AI-driven molecular diversification and ligand-based optimization of macitentan derivatives targeting VEGFR1 and endothelin signaling pathways.

PloS one·2026
Same journal

Performance patterns and records in the world aquatics masters championships: Where do the most frequently represented nations among the top-ten masters swimmers come from?

PloS one·2026
Same journal

Modeling diurnal Temperature-Rainfall relationships under multicollinearity using PLS-SEM: A case study of Ghana.

PloS one·2026
Same journal

Organizational culture, social capital, and emergency capacity in primary healthcare institutions: A cross-sectional structural equation modeling study comparing ordinary and older communities.

PloS one·2026
Same journal

Impact of kidney function on the metabolome in the general population.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.8K

An Algorithm to Automatically Generate the Combinatorial Orbit Counting Equations.

Ine Melckenbeeck1, Pieter Audenaert1, Tom Michoel2

  • 1Department of Information Technology (INTEC), Ghent University-iMinds, Ghent, Belgium.

Plos One
|January 23, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces automated methods to count graphlets (small subgraphs) in large networks. New techniques enable automatic equation generation and graphlet naming for up to six vertices, improving graph analysis efficiency.

More Related Videos

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence
12:34

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence

Published on: June 24, 2016

10.7K
Accurate Follicle Enumeration in Adult Mouse Ovaries
07:27

Accurate Follicle Enumeration in Adult Mouse Ovaries

Published on: October 16, 2020

9.9K

Related Experiment Videos

Last Updated: Mar 26, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.8K
Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence
12:34

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence

Published on: June 24, 2016

10.7K
Accurate Follicle Enumeration in Adult Mouse Ovaries
07:27

Accurate Follicle Enumeration in Adult Mouse Ovaries

Published on: October 16, 2020

9.9K

Area of Science:

  • Graph Theory
  • Network Analysis
  • Computational Mathematics

Background:

  • Graphlets are fundamental units for understanding local graph structures.
  • Counting graphlets is crucial for network analysis but computationally intensive.
  • Existing methods for counting graphlets are limited to smaller sizes (4-5 nodes).

Purpose of the Study:

  • To develop automated techniques for generating equations to count graphlets.
  • To establish a systematic naming convention for graphlets of any size.
  • To extend the capability of counting graphlets to larger sizes (e.g., 6 vertices).

Main Methods:

  • An automatic equation generation technique for graphlet counting.
  • A novel method for assigning a unique ordering and name to each graphlet.
  • Application of these techniques to derive equations for 4, 5, and 6-vertex graphlets.

Main Results:

  • Successfully generated equations for counting graphlets with 4, 5, and 6 vertices.
  • Introduced an automated system for equation generation, reducing manual effort.
  • Developed a scalable graphlet naming system applicable to any graphlet size.

Conclusions:

  • The presented techniques significantly enhance the efficiency and scope of graphlet-based network analysis.
  • Automated equation generation and graphlet naming pave the way for analyzing larger and more complex graph structures.
  • This work provides valuable tools for researchers in network science and related fields.