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Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
Cis-regulatory Sequences02:02

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...
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...
Hybrid Zones02:29

Hybrid Zones

Hybrid zones are narrow regions where two closely related species interact, mate, and produce hybrids. Relative to either parent species, hybrids may possess distinct phenotypic or genetic differences that impact their survival and reproductive success. The genetic variances introduced by hybridization influence species diversity and speciation processes within the hybrid zone.Gene flow and natural selection are evolutionary mechanisms that shape the outcome of a hybrid zone. Gene flow...
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...
Global Regulatory Systems01:28

Global Regulatory Systems

Global regulatory systems in bacteria enable rapid and coordinated responses to environmental changes by integrating sensory inputs with gene expression, ensuring efficient adaptation to fluctuating conditions. Key global regulatory mechanisms include regulons, two-component systems, sigma factors, and secondary messengers.Regulons and Global RegulatorsA regulon is a collection of genes and operons controlled by a common global regulator. These regulators enable bacteria to prioritize resource...

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Related Experiment Video

Updated: Jun 14, 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

Gene regulatory networks modelling using a dynamic evolutionary hybrid.

Ioannis A Maraziotis1, Andrei Dragomir, Dimitris Thanos

  • 1Institute of Molecular Biology, Genetics and Biotechnology, Biomedical Research Foundation, Academy of Athens, 4 Soranou Efesiou Street, Athens 11527, Greece.

BMC Bioinformatics
|March 20, 2010
PubMed
Summary

This study introduces an evolutionary trained neuro-fuzzy recurrent network (ENFRN) to infer gene regulatory networks. The ENFRN method effectively identifies gene relations and their regulation types, validated in yeast datasets.

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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:

  • Systems Biology
  • Computational Biology
  • Bioinformatics

Background:

  • Gene regulatory network inference is crucial for understanding cellular processes.
  • High-dimensional, noisy gene expression data presents challenges for network reconstruction.
  • Existing computational methods struggle with data complexity and temporal dynamics.

Purpose of the Study:

  • To develop a novel computational approach for reconstructing gene regulatory networks.
  • To identify potential gene regulators and characterize their regulatory relationships.
  • To address challenges posed by noisy and high-dimensional gene expression data.

Main Methods:

  • Utilized a novel multi-layer evolutionary trained neuro-fuzzy recurrent network (ENFRN).
  • Employed a recurrent, self-organizing structure with evolutionary training.
  • Leveraged fuzzy logic to mitigate noise-related issues in gene expression data.

Main Results:

  • The ENFRN optimized the pool of regulatory relations, assigning confidence scores to each.
  • Successfully identified biologically validated gene regulatory relations in yeast datasets.
  • Demonstrated robustness against noise and data complexity.

Conclusions:

  • The ENFRN approach effectively retrieves biologically valid regulatory relations.
  • Provides meaningful insights into the dynamics of gene regulatory networks.
  • Implemented algorithms are available as a Matlab toolbox for broader accessibility.