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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...
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...
What is Gene Expression?01:42

What is Gene Expression?

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.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
What is Gene Expression?01:36

What is Gene Expression?

A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then processed and...
What is Gene Expression?01:42

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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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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...

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Processing of Primary Brain Tumor Tissue for Stem Cell Assays and Flow Sorting
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Published on: September 25, 2012

Multiscale stochastic modelling of gene expression.

Pavol Bokes1, John R King, Andrew T A Wood

  • 1Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, UK. pavol.bokes@fmph.uniba.sk

Journal of Mathematical Biology
|October 8, 2011
PubMed
Summary
This summary is machine-generated.

This study simplifies complex gene regulatory network models using asymptotic methods. The research analyzes how these reduced models accurately represent stochastic gene expression dynamics.

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Area of Science:

  • Systems Biology
  • Computational Biology
  • Biophysics

Background:

  • Gene regulatory networks (GRNs) exhibit stochasticity, often modeled by the chemical master equation (CME).
  • CME models can become computationally intractable due to the large number of states, especially for systems with high molecule counts or fast reaction kinetics.

Purpose of the Study:

  • To develop and present a systematic procedure for reducing complex CME models of GRNs.
  • To analyze the relationship between the original CME and the simplified, reduced models.

Main Methods:

  • Application of asymptotic methods to simplify the CME.
  • Analysis of model reduction techniques for systems with disparate timescales or molecule numbers.
  • Illustrative examples of the reduction procedure on representative GRN models.

Main Results:

  • Demonstration that asymptotic methods can effectively reduce the dimensionality and complexity of CME models.
  • Identification of conditions under which model reduction is valid and preserves essential dynamics.
  • Characterization of the approximations introduced by the reduction methods.

Conclusions:

  • Reduced models offer a computationally efficient alternative for studying stochastic gene expression.
  • The presented methods provide a framework for simplifying complex biological network models.
  • Understanding the relationship between reduced and original models is crucial for accurate interpretation of results.