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Related Concept Videos

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...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Genetic Screens02:46

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which result in visible changes...
Graphs of Two-Variable Functions01:27

Graphs of Two-Variable Functions

A weather map provides a practical example of a function of two variables. Across a wide region such as the United States, temperatures vary from one location to another. Each location can be identified by two geographic coordinates: longitude and latitude. Since a single temperature value is assigned to each coordinate pair, the situation can be represented mathematically as a function with two inputs and one output.In mathematical notation, longitude and latitude can be labeled as x and y,...
Protein Networks02:26

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
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Related Experiment Video

Updated: Jul 3, 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

Dynamic visualization of coexpression in systems genetics data.

Joshua New1, Wesley Kendall, Jian Huang

  • 1Department of Electrical Engineering & Computer Science, University of Tennesee, Knoxville, TN 37996, USA. new@cs.utk.edu

IEEE Transactions on Visualization and Computer Graphics
|July 5, 2008
PubMed
Summary
This summary is machine-generated.

Interactive visualization tools help biologists analyze complex gene co-expression data. This system integrates graph theory and novel interfaces for intuitive biological network exploration and hypothesis generation.

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Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
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Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Related Experiment Videos

Last Updated: Jul 3, 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

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05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine
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Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

Area of Science:

  • Bioinformatics
  • Systems Biology
  • Computational Biology

Background:

  • Modern high-throughput techniques generate vast biological datasets.
  • Integrating and visualizing complex biological data, such as gene co-expression, remains a challenge for researchers.
  • Effective data assimilation is crucial for addressing grand scientific challenges.

Purpose of the Study:

  • To develop novel interactive visualization tools for gene co-expression analysis.
  • To enable dynamic hypothesis formulation and parameter sensitivity evaluation.
  • To facilitate an intuitive understanding of biological network structures and critical gene identification.

Main Methods:

  • Utilizing graphs to represent gene expression correlation.
  • Integrating techniques including graph layout, qualitative and quantitative subgraph extraction, and dynamic level-of-detail abstraction.
  • Employing a novel 2D user interface and template-based fuzzy classification.

Main Results:

  • The developed system provides innovative analytical capabilities for gene co-expression data.
  • Demonstrated effectiveness using a real-world workflow from a large-scale mammalian systems genetics study.
  • Facilitates discovery of genes in critical network positions and pathways.

Conclusions:

  • Interactive visualization is essential for leveraging high-throughput biological data.
  • The integrated system enhances the analysis of gene co-expression networks.
  • Supports biological discovery by improving understanding of complex genetic interactions.