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

Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

1.5K
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...
1.5K
What is Gene Expression?01:42

What is Gene Expression?

198.5K
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...
198.5K
What is Gene Expression?01:36

What is Gene Expression?

11.9K
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...
11.9K
What is Gene Expression?01:42

What is Gene Expression?

33.9K
33.9K
Ribosome Profiling02:24

Ribosome Profiling

4.3K
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
4.3K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

5.7K
5.7K

You might also read

Related Articles

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

Sort by
Same author

Large Language Models for Semantic Interoperability in Value-Based Perioperative Care.

Journal of medical systems·2026
Same author

TikTok is a valuable data source for tracking the opioid crisis.

NPJ digital medicine·2026
Same author

Drug-Target Interaction Prediction with PIGLET.

bioRxiv : the preprint server for biology·2026
Same author

GATSBI: Improving context-aware protein embeddings through biologically motivated data splits.

bioRxiv : the preprint server for biology·2026
Same author

Secure bioinformatics: privacy-preserving federated analytics using homomorphic encryption.

Bioinformatics (Oxford, England)·2026
Same author

Biological data governance in an age of AI.

Science (New York, N.Y.)·2026
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Mar 12, 2026

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
09:13

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Published on: January 13, 2016

8.4K

Imputing gene expression to maximize platform compatibility.

Weizhuang Zhou1, Lichy Han2, Russ B Altman1,3

  • 1Department of Bioengineering.

Bioinformatics (Oxford, England)
|November 1, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a gene expression inference model to predict values for genes unique to the Affymetrix HG-U133 Plus 2.0 platform. The model enhances downstream analysis by expanding the feature space using common genes from both HG-U133A and HG-U133 Plus 2.0 platforms.

More Related Videos

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

639
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

14.1K

Related Experiment Videos

Last Updated: Mar 12, 2026

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform
09:13

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

Published on: January 13, 2016

8.4K
A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
06:02

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells

Published on: October 28, 2025

639
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

14.1K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Gene Expression Analysis

Background:

  • Gene Expression Omnibus (GEO) hosts vast biological data, crucial for hypothesis generation and statistical power.
  • Affymetrix HG-U133A and HG-U133 Plus 2.0 are prevalent human microarray platforms in GEO.
  • Comparing data across different platforms is challenging due to probe set differences, often leading to data exclusion.

Purpose of the Study:

  • To develop a gene expression inference model to predict expression values for genes unique to the HG-U133 Plus 2.0 platform.
  • To leverage common genes between HG-U133A and HG-U133 Plus 2.0 platforms for accurate imputation.
  • To enhance downstream analysis by utilizing an enlarged feature space.

Main Methods:

  • Constructed gene expression inference models using genes common to both HG-U133A and HG-U133 Plus 2.0 platforms.
  • Validated model performance against controlled replicate studies and measured data.
  • Applied the model to six independent studies to assess its impact on downstream analysis.

Main Results:

  • The developed model accurately predicts gene expression values within observed variability.
  • Predicted values show high correlation with measured gene expression data.
  • Utilizing the enlarged feature space significantly improved downstream analysis performance across multiple studies.

Conclusions:

  • The gene expression inference model effectively imputes missing data for unique probes on the HG-U133 Plus 2.0 platform.
  • This approach maximizes the utility of GEO data by integrating information from different microarray platforms.
  • The affyImpute R package provides a valuable tool for researchers analyzing Affymetrix microarray data.