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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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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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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

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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.
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Related Experiment Video

Updated: Feb 13, 2026

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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Identification of spatial expression trends in single-cell gene expression data.

Daniel Edsgärd1,2, Per Johnsson1,2, Rickard Sandberg1,2

  • 1Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.

Nature Methods
|March 20, 2018
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Summary

New computational methods are needed for spatial gene expression analysis. trendsceek identifies genes with significant spatial expression trends using marked point processes, revealing expression gradients and hot spots.

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Area of Science:

  • Computational biology
  • Genomics
  • Bioinformatics

Background:

  • Advancements in single-cell spatial gene expression measurement necessitate novel computational analysis strategies.
  • Analyzing spatial transcriptomic and fluorescence in situ hybridization data requires robust computational tools.

Purpose of the Study:

  • To introduce trendsceek, a novel computational method for identifying genes with statistically significant spatial expression trends.
  • To demonstrate the utility of trendsceek in analyzing diverse spatial gene expression datasets.

Main Methods:

  • The study presents trendsceek, a method grounded in marked point processes.
  • trendsceek is applied to spatial transcriptomic and sequential fluorescence in situ hybridization data.
  • The method also analyzes low-dimensional projections of single-cell RNA-seq data.

Main Results:

  • trendsceek successfully identifies genes exhibiting statistically significant spatial expression trends.
  • The method reveals significant gene expression gradients within spatial datasets.
  • trendsceek detects significant gene expression hot spots in various data types.

Conclusions:

  • trendsceek provides a powerful computational approach for analyzing spatial gene expression patterns.
  • The method enhances the understanding of gene expression organization in tissues.
  • trendsceek is applicable to a range of single-cell spatial genomics data.