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Related Concept Videos

Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
Regulation of Expression Occurs at Multiple Steps02:24

Regulation of Expression Occurs at Multiple Steps

Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
Transcription results in the generation of precursor (pre-mRNA) that consists of both exons and introns, which needs further processing before being translated to a...
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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
Structure of a Gene01:30

Structure of a Gene

A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...
Operon Model01:23

Operon Model

The operon model represents a fundamental mechanism of gene regulation in prokaryotes, enabling coordinated expression of genes involved in related metabolic or functional pathways. Operons consist of structural genes, a promoter, and an operator, with transcription regulated by repressors, activators, and small effector molecules.Structure and Function of OperonsAn operon is a cluster of structural genes transcribed together under the control of a single promoter. The promoter region...

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Related Experiment Video

Updated: Jul 11, 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

A framework for elucidating regulatory networks based on prior information and expression data.

Olivier Gevaert1, Steven Van Vooren, Bart De Moor

  • 1Katholieke Universiteit Leuven, Department of Electrical Engineering (ESAT), Kasteelpark Arenberg 10, 3001 Leuven, Belgium. olivier.gevaert@esat.kuleuven.be

Annals of the New York Academy of Sciences
|October 11, 2007
PubMed
Summary

This study integrates PubMed abstracts and protein-DNA interactions into Bayesian networks to simplify the modeling of gene regulatory networks. This approach enhances model robustness and reliability for bioinformatics research.

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

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Elucidating gene regulatory networks is crucial in bioinformatics.
  • Integrating diverse data sources can improve the accuracy of network modeling.
  • Current methods face challenges in complexity and reliability.

Purpose of the Study:

  • To propose a novel approach for modeling regulatory networks using Bayesian networks.
  • To incorporate multiple information sources as structural priors in Bayesian networks.
  • To enhance the robustness and reliability of reverse-engineered regulatory networks.

Main Methods:

  • Utilizing PubMed abstracts and public taxonomies/ontologies as information sources.
  • Incorporating known protein-DNA interactions as complementary information.
  • Employing Bayesian networks for data integration and network structure prior.
  • Investigating the combined and separate effects of these information sources.

Main Results:

  • The proposed method reduces the complexity of reverse-engineering regulatory networks.
  • Incorporating information priors leads to more robust and reliable network models.
  • The Bayesian network framework facilitates effective data integration.

Conclusions:

  • Bayesian networks offer a powerful framework for integrating diverse data in regulatory network modeling.
  • The approach is extensible to include additional data sources.
  • This method provides a more reliable way to model complex biological systems.