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Related Concept Videos

What is Gene Expression?01:42

What is Gene Expression?

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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...
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What is Gene Expression?01:36

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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...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

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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)
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mRNA Stability and Gene Expression02:51

mRNA Stability and Gene Expression

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The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity.
Cis-acting Elements involved in mRNA stability
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Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
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Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

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Differential Coexpression Network Analysis for Gene Expression Data.

Bao-Hong Liu1,2

  • 1State Key Laboratory of Veterinary Etiological Biology; Key Laboratory of Veterinary Parasitology of Gansu Province; Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Lanzhou, Gansu Province, People's Republic of China. liubaohong@caas.cn.

Methods in Molecular Biology (Clifton, N.J.)
|March 15, 2018
PubMed
Summary
This summary is machine-generated.

Differential coexpression analysis reveals gene interactions missed by traditional methods. This approach identifies molecular markers for various conditions, including cancer, by examining gene networks.

Keywords:
CoexpressionDifferential coexpression network

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Gene expression profiling identifies molecular variations.
  • Traditional analysis overlooks gene interactions, focusing on individual genes.
  • Gene functions arise from complex interactions within biological networks.

Purpose of the Study:

  • To introduce differential coexpression analysis as a powerful approach.
  • To complement conventional differential expression analysis.
  • To identify gene markers at a systems level.

Main Methods:

  • Gene coexpression network construction.
  • Differential coexpression network analysis.
  • Comparison of network topology, module identification, and differential gene pair identification.

Main Results:

  • Differential coexpression analysis identifies gene markers missed by traditional methods.
  • This approach provides a systems-level perspective on gene regulation.
  • Applications span environmental stress, genetic variation, and disease research.

Conclusions:

  • Differential coexpression analysis offers a robust framework for understanding gene interactions.
  • It is widely applicable in diverse biological and medical research areas.
  • The methods discussed have significant implications for cancer research.