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

Nodal Analysis01:10

Nodal Analysis

Nodal analysis is a fundamental method in electrical engineering used to simplify the process of circuit analysis. This method revolves around the concept of using node voltages as the primary variables for circuit analysis. The objective is to determine the voltage at each node in a circuit, which can then be used to find other quantities of interest, such as currents through specific components.
Consider, for instance, a simple circuit composed of three nodes and three resistors, as shown in...
Nodal Analysis with Voltage Sources01:11

Nodal Analysis with Voltage Sources

Nodal analysis is a remarkably effective method used in electrical engineering to simplify the analysis of complex circuits, including those with dependent or independent voltage sources. Its strength lies in its systematic approach to breaking down circuits into manageable components, making it easier for engineers to understand and solve.
Consider a circuit that contains four resistors and two voltage sources, as shown in Figure 1. One of these voltage sources is connected between a...
pV-Diagrams01:18

pV-Diagrams

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...
Time-Series Graph00:54

Time-Series Graph

A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
Econometric Views (EViews)01:29

Econometric Views (EViews)

Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

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...

You might also read

Related Articles

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

Sort by
Same author

Dual-Functional PA-CDs: A High-Performance Material for Metal Corrosion Monitoring and Corrosion Inhibition.

Materials (Basel, Switzerland)·2026
Same author

Altered brain-behavior coupling during inhibitory control in ankylosing spondylitis: ERP evidence from NoGo-P3 component.

PloS one·2026
Same author

Accuracy of 8 Modern Intraocular Lens Power Calculation Formulas in Asian Eyes With Axial Length ≥ 32.00 mm.

American journal of ophthalmology·2026
Same author

Coexistence of bla<sub>NDM-1</sub>, bla<sub>KPC-2</sub> and tmexCD2-toprJ2 in clinical ST1545 Klebsiella pneumoniae from China.

International journal of antimicrobial agents·2026
Same author

Multidimensional additive manufacturing micro/nanorobots: from elaborate design to smart cargo delivery.

Nanoscale horizons·2026
Same author

Analysis of Japanese Encephalitis Vector Ecology, Host Serology, and Viral Genetic Characteristics in Hunan Province, China.

Vector borne and zoonotic diseases (Larchmont, N.Y.)·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: May 19, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

Enabling dynamic network analysis through visualization in TVNViewer.

Ross E Curtis1, Jing Xiang, Ankur Parikh

  • 1Joint Carnegie Mellon, University of Pittsburgh PhD Program in Computational Biology, Pittsburgh, PA, USA.

BMC Bioinformatics
|August 18, 2012
PubMed
Summary
This summary is machine-generated.

TVNViewer visualizes dynamic biological networks, aiding the interpretation of complex molecular changes over time. This tool enhances understanding of context-dependent biological processes and network rewiring.

More Related Videos

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

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
11:29

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Related Experiment Videos

Last Updated: May 19, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

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

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
11:29

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Biological processes exhibit context- and time-dependency, leading to evolving molecular interactions.
  • Analyzing dynamic networks and their rewiring is challenging despite advances in machine learning.
  • Information visualization offers a powerful approach for exploratory analysis of complex biological data.

Purpose of the Study:

  • To introduce TVNViewer, a novel visualization tool designed for dynamic network analysis.
  • To demonstrate the utility of TVNViewer in exploring and interpreting biological networks that change over time or across different environments.

Main Methods:

  • Development of TVNViewer, a specialized software for visualizing dynamic networks.
  • Application of TVNViewer to analyze real-world biological datasets, including yeast cell cycle and breast cancer progression.

Main Results:

  • TVNViewer effectively visualizes dynamic network structures and rewiring patterns.
  • Analysis of yeast cell cycle and breast cancer progression datasets showcased the tool's capability in revealing temporal and contextual biological insights.

Conclusions:

  • TVNViewer is a potent tool for analyzing dynamic biological networks.
  • The visualization techniques employed by TVNViewer facilitate the understanding of networks that vary across time and space.