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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

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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. 
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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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Updated: Jan 31, 2026

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
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Insights Into Systemic Sclerosis from Gene Expression Profiling.

Jennifer M Franks1,2,3, Michael L Whitfield1,2,4,5

  • 1Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.

Current Treatment Options in Rheumatology
|January 30, 2026
PubMed
Summary
This summary is machine-generated.

Genomic data science, particularly transcriptomics, reveals molecular patterns in systemic sclerosis (SSc). This approach enhances understanding of disease heterogeneity and guides personalized treatment strategies for SSc patients.

Keywords:
Artificial intelligenceBiomarkersDNA microarrayGene expressionGenomicsMachine learningRNA-seqSingle-cell genomicsSystemic autoimmune diseaseSystemic sclerosis

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Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
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Area of Science:

  • Genomic data science
  • Molecular biology
  • Immunology

Background:

  • Systemic sclerosis (SSc) is a complex autoimmune disease with significant heterogeneity.
  • Understanding this heterogeneity is crucial for effective treatment and management.
  • Genomic data science offers novel approaches to dissect disease complexity.

Purpose of the Study:

  • To review the application of transcriptomics in understanding systemic sclerosis (SSc) heterogeneity.
  • To explore how molecular insights from transcriptomics can inform treatment decisions.
  • To highlight the role of single-cell technologies in SSc research.

Main Methods:

  • Analysis of bulk and single-cell transcriptomic data from SSc patients.
  • Integration and analysis of publicly available genomic datasets.
  • Examination of gene expression patterns and cellular interactions.

Main Results:

  • Transcriptomics identifies reproducible gene expression patterns in SSc, offering insights into etiology.
  • These patterns suggest potential patient stratification for targeted therapies.
  • Single-cell technologies are revealing the roles of specific cell types in SSc pathogenesis.
  • Interactions between immune and stromal cells are implicated in disease progression.

Conclusions:

  • Molecular quantification of SSc heterogeneity is achievable through transcriptomics.
  • Further research into cellular and molecular dynamics will improve disease management.
  • Personalized, data-driven treatment decisions are the future for SSc patients.