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

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.5K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.5K
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

15.4K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
15.4K
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

434
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
434
Stability of structures01:14

Stability of structures

657
In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...
657
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.3K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
4.3K
Quadratic Models01:23

Quadratic Models

364
Quadratic models are mathematical representations used to describe relationships in which the rate of change changes at a constant rate. These models appear in a wide variety of natural and engineered systems, especially those involving motion, forces, and optimization. One common application is analyzing the vertical motion of objects influenced by gravity, such as a ball thrown into the air.In such scenarios, the object's height changes over time in a curved pattern, rising to a maximum point...
364

You might also read

Related Articles

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

Sort by
Same author

Speeding Up the Discovery of Optimal Feature Combinations for Omics Data Based on Pseudo-Kernel Function.

Research square·2026
Same author

Semi-Supervised Traffic Sign Detection with Dynamic Pseudo-Label Selection and Gated Feature Fusion-Based Proposal Refinement.

Sensors (Basel, Switzerland)·2026
Same author

Targeting octopamine synthesis genes LsTDC and LsTβH impairs reproduction, feeding and virus transmission in the small brown planthopper Laodelphax striatellus.

Pest management science·2026
Same author

Organic Electrochemical Transformations of Resource Small Molecules.

Accounts of chemical research·2026
Same author

Electrochemical hydroxylation of alkenes with H<sub>2</sub>O.

National science review·2026
Same author

Semi-Supervised Traffic Sign Detection with Dual Confidence Fusion Module and Structured Block-Regularized Neck.

Sensors (Basel, Switzerland)·2026
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Apr 23, 2026

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

2.1K

Uncovering community structures with initialized Bayesian nonnegative matrix factorization.

Xianchao Tang1, Tao Xu2, Xia Feng2

  • 1School of Computer Science and Technology, Tianjin University, Tianjin, China.

Plos One
|October 1, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian nonnegative matrix factorization method for identifying community structures in complex networks. The approach provides accurate and efficient community detection, overcoming limitations of existing algorithms.

More Related Videos

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

876
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K

Related Experiment Videos

Last Updated: Apr 23, 2026

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts
08:51

Author Spotlight: Integrated Multi-Omics Analysis for Unveiling Multicellular Immune Signatures in Clinical Heart Attack Cohorts

Published on: September 20, 2024

2.1K
Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

876
Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.7K

Area of Science:

  • Network science
  • Data mining
  • Machine learning

Background:

  • Identifying community structures is crucial for understanding complex networks.
  • Existing nonnegative matrix factorization algorithms for community detection suffer from unstable results and inefficiency.
  • There is a need for improved methods for accurate and efficient community discovery.

Purpose of the Study:

  • To propose a novel initialized Bayesian nonnegative matrix factorization model for community membership determination.
  • To address the drawbacks of existing algorithms, including instability and inefficiency.
  • To enhance the accuracy and performance of community detection in complex networks.

Main Methods:

  • Utilizing singular value decomposition (SVD) for initial matrix factorization.
  • Applying Bayesian nonnegative matrix factorization (BNMF) with initialized matrices.
  • Determining community structure by classifying nodes based on the final matrix factorization.

Main Results:

  • The proposed method achieves high accuracy in community detection.
  • Experimental results demonstrate competitive performance compared to state-of-the-art methods.
  • The approach provides stable and efficient community structure discovery.

Conclusions:

  • The initialized Bayesian nonnegative matrix factorization model is effective for uncovering community structures.
  • This method offers an accurate and efficient alternative to existing community detection algorithms.
  • The approach successfully determines community membership in complex networks.