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Related Concept Videos

Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Regulation of Expression Occurs at Multiple Steps02:24

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Gene expression can be regulated at almost every step from gene to protein. Transcription is the step that is most commonly regulated. This involves the binding of proteins to short regulatory sequences on the DNA. This association can either promote or inhibit the transcription of a gene associated with the respective sequence.
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Ribosome Profiling02:24

Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
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Constitutive and Regulated Gene Expression01:27

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Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...
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Related Experiment Video

Updated: Mar 5, 2026

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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EXPath tool-a system for comprehensively analyzing regulatory pathways and coexpression networks from high-throughput

Han-Qin Zheng1, Nai-Yun Wu1, Chi-Nga Chow1

  • 1Institute of Tropical Plant Sciences, College of Biosciences and Biotechnology, National Cheng Kung University, Tainan 701, Taiwan.

DNA Research : an International Journal for Rapid Publication of Reports on Genes and Genomes
|March 25, 2017
PubMed
Summary
This summary is machine-generated.

The EXPath Tool offers a user-friendly webserver for analyzing gene expression data from next-generation sequencing (NGS) and microarrays. It helps identify key genes and pathways, aiding in understanding experimental treatment effects.

Keywords:
NGSbiological pathwayco-expression network

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Next-generation sequencing (NGS) generates vast gene expression data, requiring advanced analysis tools.
  • Existing systems lack comprehensive analysis capabilities for post-gene annotation transcriptome data.
  • Efficient mining of significant genes and regulatory pathways from high-throughput data is crucial.

Purpose of the Study:

  • To develop a user-friendly webserver, EXPath Tool, for comprehensive analysis of gene expression profiles.
  • To enable pathway annotation and comparative analysis for microarray and NGS data across various organisms.
  • To facilitate the inference of metabolic pathways and treatment effects from transcriptome data.

Main Methods:

  • Developed EXPath Tool, a webserver for pathway annotation and comparative analysis of gene expression data.
  • Integrated functions for accessing gene expression patterns, identifying co-expression genes, and dissecting differentially expressed genes (DEGs).
  • Implemented pathway and Gene Ontology (GO) enrichment analysis, and co-expression network construction.

Main Results:

  • EXPath Tool supports analysis of user-customized gene expression profiles from various platforms.
  • The tool enables DEGs search, pathway/GO enrichment analysis, and co-expression analysis.
  • A case study on IAA-responsive genes demonstrated efficient identification of critical hub genes.

Conclusions:

  • EXPath Tool provides a comprehensive solution for analyzing high-throughput transcriptome data.
  • The system effectively aids in inferring metabolic pathways and understanding treatment effects.
  • EXPath Tool facilitates the identification of key genes and regulatory networks in biological studies.