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What is Gene Expression?01:42

What is Gene Expression?

197.1K
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

What is Gene Expression?

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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)
The 3-dimensional positioning of chromatin in the nucleus influences the...
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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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Related Experiment Video

Updated: Feb 13, 2026

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish
11:42

Sample Preparation and Analysis of RNASeq-based Gene Expression Data from Zebrafish

Published on: October 27, 2017

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SPSNet: subpopulation-sensitive network-based analysis of heterogeneous gene expression data.

Abha Belorkar1,2, Rajanikanth Vadigepalli3, Limsoon Wong4

  • 1School of Computing, National University of Singapore, 13 Computing Drive, Singapore, 117417, Singapore.

BMC Systems Biology
|March 22, 2018
PubMed
Summary

This study introduces SPSNet, a new method to find hidden sample subtypes in gene expression data. SPSNet identifies biological pathway subnetworks to reveal underlying subphenotypes and handle technical noise.

Keywords:
Differential expression analysisGene expressionHeterogeneitySPSNet

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Transcriptomic datasets often exhibit undeclared heterogeneity from biological and technical variations.
  • Current analysis methods struggle with sample heterogeneity, limiting subphenotype discovery.
  • Existing unsupervised methods for subtype identification often yield irreproducible results.

Purpose of the Study:

  • To develop a novel method for identifying subtype-specific gene expression signatures.
  • To capture the diversity of underlying biological mechanisms and potential sample subphenotypes.
  • To address both biological and technical sources of heterogeneity in transcriptomic data.

Main Methods:

  • SPSNet analyzes gene expression data by focusing on the activity of subnetworks within biological pathways.
  • The method identifies gene subnetworks that capture biological diversity and potential subphenotypes.
  • SPSNet can also identify subnetworks affected by technical variations like batch effects.

Main Results:

  • SPSNet consistently uncovers meaningful patterns of heterogeneity across multiple public datasets.
  • The method effectively identifies subphenotypes originating from diverse biological and technical sources.
  • Demonstrated performance of SPSNet as a sensitive and reliable tool for heterogeneity analysis.

Conclusions:

  • SPSNet is a robust method for uncovering hidden heterogeneity in gene expression data.
  • The approach aids in understanding the structure and nature of biological and technical variations.
  • SPSNet facilitates the discovery of biologically relevant subphenotypes previously obscured by data complexity.