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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...
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...
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...

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Related Experiment Video

Updated: Jul 17, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray

Abdallah Sayyed-Ahmad1, Kagan Tuncay, Peter J Ortoleva

  • 1Center for Cell and Virus Theory, Department of Chemistry, Indiana University, Bloomington, IN 47405, USA. asayyeda@cems.umn.edu <asayyeda@cems.umn.edu>

BMC Bioinformatics
|January 25, 2007
PubMed
Summary

This study presents a new method for analyzing gene expression data to build transcriptional regulatory networks (TRNs). The approach uses information theory and cell modeling to quantify gene regulation and improve diagnostic and treatment discovery.

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Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
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Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
11:00

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Published on: August 8, 2013

Related Experiment Videos

Last Updated: Jul 17, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
07:23

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
11:00

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

Published on: August 8, 2013

Area of Science:

  • Systems Biology
  • Computational Biology
  • Molecular Biology

Background:

  • Gene expression data offers insights into cellular complexity, diagnosis, and treatment discovery.
  • Current methods for constructing transcriptional regulatory networks (TRNs) face challenges with data noise and sparsity.
  • Integrating gene expression data with cell modeling is crucial for understanding complex biological systems.

Purpose of the Study:

  • To develop a novel approach for constructing and quantifying TRNs using gene expression microarray data and cell modeling.
  • To integrate information theory principles for a probabilistic framework in network analysis.
  • To address challenges in TRN discovery and quantification.

Main Methods:

  • Utilized information theory and cell modeling to construct and quantify TRNs from gene expression microarray data.
  • Employed entropy maximization to determine transcription factor (TF) time courses and kinetic parameters.
  • Incorporated a physically-motivated regularization for TF time courses to handle noisy and sparse data.

Main Results:

  • The developed method provides enhanced physicochemical information complementing network structure analysis.
  • Accurate TF time courses and regulatory parameters were obtained, accounting for time delays between mRNA expression and TF activity.
  • The approach demonstrated robustness against errors in gene expression data and TRN proposals, validated in *Escherichia coli*.

Conclusions:

  • Multiplex time series data can effectively build cellular process networks and calibrate physicochemical parameters.
  • A probabilistic framework addresses uncertainties inherent in gene expression microarray data.
  • The method offers a robust tool for TRN construction and quantification, applicable to gene regulation studies.