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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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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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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.
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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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Updated: Apr 26, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
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Pathway network inference from gene expression data.

Ignacio Ponzoni, María Nueda, Sonia Tarazona

    BMC Systems Biology
    |July 18, 2014
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new computational method, Pathway Network Analysis (PANA), to map functional connections between biological pathways. PANA reveals how pathways interact, offering deeper insights into complex biological systems and disease mechanisms.

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    Area of Science:

    • Systems Biology
    • Computational Biology
    • Genomics

    Background:

    • High-throughput omics technologies enable genome-wide measurements of cellular activity, advancing Systems Biology.
    • Gene expression analysis has progressed from individual genes to pathways and interaction networks.
    • Understanding biological systems requires characterizing interactions between functional modules.

    Purpose of the Study:

    • To develop a novel computational methodology for studying functional interconnections among molecular elements in biological systems.
    • To create a global, interconnected network of pathways representing functional cross-talk.

    Main Methods:

    • The Pathway Network Analysis (PANA) approach utilizes high-throughput genomics data and functional annotation.
    • It extracts activity profiles for each pathway.
    • Machine-learning methods infer relationships between these pathway profiles.

    Main Results:

    • A global network of functional pathway interconnections was generated.
    • The approach was applied to map transcriptional connections during the yeast cell cycle.
    • Pathway connectivity changes in an Alzheimer disease model were identified.

    Conclusions:

    • PANA is a valuable tool for understanding functional interdependencies in complex biological systems.
    • The inferred network is algorithmically consistent and supported by functional data.
    • The method elucidates the molecular basis of functional connections and regulatory mechanisms.