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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
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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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Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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Pathway and Network Analysis of Differentially Expressed Genes in Transcriptomes.

Qianli Huang1, Ming-An Sun2, Ping Yan3

  • 1School of Biological and Medical Engineering, Hefei University of Technology, Hefei, China. cheneyhuang5128@gmail.com.

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Transcriptome sequencing reveals differentially expressed genes. This study compares gene set enrichment analysis with topology-based methods for pathway and network analysis from sequencing data.

Keywords:
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Area of Science:

  • Genomics and Bioinformatics
  • Molecular Biology

Background:

  • Transcriptome sequencing is widely used for gene expression profiling and identifying differentially expressed (DE) genes.
  • Gene Set (GS) enrichment analysis is common for pathway identification but ignores gene interaction networks.
  • Topology-based methods offer a more integrated approach by incorporating pathway and gene network structures.

Purpose of the Study:

  • To provide an overview of computational workflows for analyzing DE pathways and gene networks from transcriptome sequencing data.
  • To compare traditional gene set enrichment analysis with advanced topology-based methods.

Main Methods:

  • Demonstration of several recent computational workflows.
  • Application of gene set enrichment analysis.
  • Application of topology-based methods for pathway and network analysis.

Main Results:

  • Gene set enrichment analysis treats pathways as simple gene collections.
  • Topology-based methods integrate pathway structure and gene/protein interactions.
  • Comparative analysis highlights the strengths of topology-based approaches.

Conclusions:

  • Topology-based methods provide a more comprehensive analysis of pathways and networks compared to traditional GS enrichment.
  • Advanced computational workflows enhance the biological insights derived from transcriptome sequencing data.