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

Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

471
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
471
Relation between Mathematical Equations and Block Diagrams01:20

Relation between Mathematical Equations and Block Diagrams

3.9K
In a spring-mass-damper system, the second-order differential equation describes the dynamic behavior of the system. When transformed into the Laplace domain under zero initial conditions, this equation can be effectively analyzed and manipulated. The transformation into the Laplace domain converts differential equations into algebraic equations, simplifying the process of isolating the output.
3.9K
Block Diagram Reduction01:22

Block Diagram Reduction

666
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...
666
State Space Representation01:27

State Space Representation

727
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
727
Introduction to the Sign Test01:10

Introduction to the Sign Test

1.5K
The sign test is an important tool in nonparametric statistics, offering a straightforward yet effective method for analyzing matched pairs, nominal data, or hypotheses concerning the median of a population. It transforms data points into positive or negative signs, avoiding the need for assumptions about data distribution and instead focusing on the direction of change. It is particularly valuable when data does not conform to the normal distribution requirements of many parametric tests. For...
1.5K
Elements of Block Diagrams01:25

Elements of Block Diagrams

933
Block diagrams serve as a visual representation of the input-output relationships within a system. An illustrative example is a heating system, where the set temperature activates the furnace to warm the room to the desired level. Block diagrams are versatile, modeling linear systems through Laplace transform variables and nonlinear systems using time domain variables.
A block diagram typically includes essential elements such as comparators, blocks, and feedback loops. Each of these elements...
933

You might also read

Related Articles

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

Sort by
Same author

Predicting multiplex subcellular localization of proteins using protein-protein interaction network: a comparative study.

BMC bioinformatics·2012
Same author

Predicting protein function by multi-label correlated semi-supervised learning.

IEEE/ACM transactions on computational biology and bioinformatics·2012
See all related articles

Related Experiment Video

Updated: Apr 7, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K

Stochastic block model and exploratory analysis in signed networks.

Jonathan Q Jiang1

  • 1Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|July 15, 2015
PubMed
Summary

We introduce a new model for analyzing signed networks, identifying hidden community structures based on positive and negative connections. This approach reveals overlapping communities and important nodes, enhancing network analysis.

More Related Videos

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.2K
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 7, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.7K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.2K
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
  • Statistical Modeling
  • Data Mining

Background:

  • Signed networks, which include both positive and negative relationships, are prevalent in real-world systems.
  • Understanding the mesoscopic structure (communities and their interrelations) in these networks is crucial but challenging.
  • Existing models often struggle to effectively capture the dual nature of positive and negative links.

Purpose of the Study:

  • To develop a generalized stochastic block model (GSBM) for analyzing mesoscopic structures in signed networks.
  • To group vertices with similar positive and negative connection profiles into clusters.
  • To identify overlapping structures and important vertices within signed networks.

Main Methods:

  • Proposed a generalized stochastic block model (GSBM) for signed networks.
  • Modeled group memberships as hidden variables.
  • Characterized inter-group connection patterns using two block matrices (one for positive, one for negative links).
  • Fitted the model to observed network data.

Main Results:

  • Successfully extracted hidden mesoscopic structures without prior knowledge.
  • Identified overlapping community structures within signed networks.
  • Discovered two types of important vertices: group cores and inter-group bridges.
  • Demonstrated the model's effectiveness and superiority on synthetic and real-life networks.

Conclusions:

  • The proposed GSBM effectively reveals mesoscopic structures in signed networks.
  • The model provides insights into vertex roles, overlapping communities, and network topology.
  • This framework offers a powerful tool for analyzing complex signed network data.