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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the timing and level of...
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...

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Related Experiment Video

Updated: Jun 25, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Human gene expression sensitivity according to large scale meta-analysis.

Pei Hao1, Siyuan Zheng, Jie Ping

  • 1Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, PR China. phao@sibs.ac.cn

BMC Bioinformatics
|February 12, 2009
PubMed
Summary

This study introduces a framework to analyze gene expression sensitivity, revealing that robust genes are vital for essential cellular functions while sensitive genes have diverse roles. Gene expression sensitivity analysis is crucial for microarray data interpretation.

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Last Updated: Jun 25, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
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Published on: August 13, 2020

Area of Science:

  • Systems Biology
  • Genomics
  • Bioinformatics

Background:

  • Gene expression exhibits varying sensitivities to biological conditions.
  • Understanding gene expression sensitivity is critical for applications like microarray analysis.
  • Previous work by J.H. Ohn et al. explored this property using yeast transcriptional data.

Purpose of the Study:

  • To develop a computational framework for gene expression sensitivity analysis.
  • To compare the functional, centrality, and regulatory characteristics of sensitive and robust genes.

Main Methods:

  • Development of a gene expression sensitivity analysis framework.
  • Comparison of gene functions, network centralities (vertex degree, betweenness), and transcription factor regulations.
  • Integration of gene expression data with protein-protein interaction networks.

Main Results:

  • Robust genes are predominantly involved in essential cellular processes, while sensitive genes exhibit diverse functions.
  • Both sensitive and robust genes display similar geometric centrality in protein networks.
  • Robust genes possess higher vertex degree and betweenness centrality compared to sensitive genes.
  • Robust genes share fewer transcription factors as regulators than sensitive genes.

Conclusions:

  • Gene expression exhibits distinct responses to external perturbations.
  • Sensitive and robust genes play different roles within the cell.
  • Incorporating gene expression sensitivity into microarray analysis is recommended.