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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

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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...
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Regulation of Expression Occurs at Multiple Steps02:24

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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.
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Regulation of Expression at Multiple Steps01:23

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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...
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Constitutive and Regulated Gene Expression01:27

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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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Master Transcription Regulators02:23

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Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a  complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...
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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
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Phenotype Control techniques for Boolean gene regulatory networks.

Daniel Plaugher1, David Murrugarra2

  • 1Department of Toxicology and Cancer Biology, University of Kentucky, Lexington, KY, USA. plaugher_dr@uky.edu.

Bulletin of Mathematical Biology
|August 30, 2023
PubMed
Summary
This summary is machine-generated.

Boolean networks (BNs) model cell signaling for phenotype control. This review compares control methods like algebraic approaches and feedback vertex sets, using a leukemia cancer model to assess efficiency and challenges.

Keywords:
Boolean networksDiscrete dynamical systemsNetwork dynamicsPhenotype control theoryRegulatory networks

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Network Medicine

Background:

  • Boolean networks (BNs) are established for analyzing intracellular communications and molecular signaling pathways.
  • BNs offer a coarse-grained approach for understanding molecular communication and controlling system outcomes, known as phenotype control theory.

Purpose of the Study:

  • To review and compare various approaches for controlling gene regulatory networks.
  • To explore methods for enhancing the efficiency of control searches in biological networks.
  • To discuss the challenges associated with implementing control techniques in biological systems.

Main Methods:

  • Comparative analysis of control methods including algebraic methods, control kernel, feedback vertex set, and stable motifs.
  • Application of these methods to an established cancer model: T-Cell Large Granular Lymphocyte Leukemia.
  • Exploration of reduction and modularity techniques to improve control search efficiency.

Main Results:

  • The study provides a comparative discussion of different control strategies for gene regulatory networks.
  • The T-Cell Large Granular Lymphocyte Leukemia model serves as a practical case study for evaluating control methods.
  • Potential strategies for optimizing control search efficiency are explored.

Conclusions:

  • Understanding and applying control methods to biological networks, like BNs, is crucial for phenotype control.
  • The choice of control method and its efficient implementation are key challenges in systems biology.
  • Further research is needed to address computational complexity and software availability for these techniques.