Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

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?01:42

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...
Entropy within the Cell01:22

Entropy within the Cell

A living cell's primary tasks of obtaining, transforming, and using energy to do work may seem simple. However, the second law of thermodynamics explains why these tasks are harder than they appear. None of the energy transfers in the universe are completely efficient. In every energy transfer, some amount of energy is lost in a form that is unusable. In most cases, this form is heat energy. Thermodynamically, heat energy is defined as the energy transferred from one system to another that is...
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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Metagenome-scale Modeling to Assess Microbiome Metabolic Complementarity for Precision Microbiota Transplantation Therapies.

bioRxiv : the preprint server for biology·2026
Same author

Minimax entropy: The statistical physics of optimal models.

Physical review. E·2026
Same author

Non-equilibrium strategies enabling ligand specificity by signaling receptors.

eLife·2025
Same author

Directional Sensing by Eukaryotic Receptors.

bioRxiv : the preprint server for biology·2024
Same author

GENERALIST: A latent space based generative model for protein sequence families.

PLoS computational biology·2023
Same author

EMBED: Essential MicroBiomE Dynamics, a dimensionality reduction approach for longitudinal microbiome studies.

NPJ systems biology and applications·2023
Same journal

Anisotropic unbinding and location-dependent hovering of a kinesin motor head over microtubule.

Biophysical journal·2026
Same journal

Kinesin-5/Cut7 C-terminal tail phosphorylation influence on motor regulation through multi-scale molecular modeling.

Biophysical journal·2026
Same journal

Dynamic conformations of fluorophores on self-labeling protein tags.

Biophysical journal·2026
Same journal

Different actions of RyR2 open and closed channel block explained by a multiscale Ca<sup>2+</sup> release model.

Biophysical journal·2026
Same journal

Membrane Environment Sets the Functional pK<sub>a</sub> of Ionizable Lipids.

Biophysical journal·2026
Same journal

Distinguishable spreading dynamics in microbial communities.

Biophysical journal·2026
See all related articles

Related Experiment Video

Updated: May 10, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

Quantifying extrinsic noise in gene expression using the maximum entropy framework.

Purushottam D Dixit1

  • 1Biosciences Department, Brookhaven National Laboratory, Upton, New York, USA. pdixit@bnl.gov

Biophysical Journal
|June 25, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a maximum entropy framework to distinguish intrinsic and extrinsic influences on gene expression noise. The method explains wider-than-Poisson mRNA distributions in E. coli by accounting for extrinsic factor variations.

More Related Videos

Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

Related Experiment Videos

Last Updated: May 10, 2026

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

Area of Science:

  • Molecular Biology
  • Systems Biology
  • Biophysics

Background:

  • Gene expression exhibits inherent noise, making it challenging to distinguish between intrinsic (within-cell) and extrinsic (between-cell) sources of variation.
  • Understanding these noise sources is crucial for deciphering gene regulation and cellular function.

Purpose of the Study:

  • To develop a novel framework for separating intrinsic and extrinsic contributions to gene expression noise using only expression profile data.
  • To quantify the impact of extrinsic factors on the probability distribution of gene product (mRNA or protein) copy numbers.

Main Methods:

  • A maximum entropy approach was employed to estimate the distribution of extrinsic factors influencing gene expression.
  • The framework was applied to model mRNA transcription from a constitutive promoter in Escherichia coli.
  • Numerical simulations of a gene expression scheme incorporating extrinsic factor variations were used for validation.

Main Results:

  • Extrinsic factors significantly influence both the qualitative and quantitative aspects of gene product probability distributions.
  • The proposed framework successfully explains the observed wider-than-Poisson distribution of mRNA copy numbers in E. coli.
  • The framework's predictions were validated against existing experimental data and numerical simulations.

Conclusions:

  • The maximum entropy framework provides a robust method for dissecting gene expression noise.
  • Variations in extrinsic factors are a key contributor to the high variability observed in mRNA copy numbers.
  • The framework is applicable to more complex gene expression systems and offers testable predictions for future research.