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Related Experiment Video

Updated: Jul 2, 2026

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
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Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration.

Yulan Liang1, Arpad Kelemen

  • 1Department of Organizational Systems and Adult Health, University of Maryland, 655 W, Lombard Street, Baltimore, MD 21201-1579, USA. ylian001@umaryland.edu

BMC Bioinformatics
|August 30, 2008
PubMed
Summary

This study analyzed gene expression across multiple tissues over time, identifying common genes and their varied responses. Liver tissue showed the most significant gene expression changes, offering insights for drug development.

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Area of Science:

  • Genomics and Bioinformatics
  • Systems Biology
  • Pharmacogenomics

Background:

  • Analysis of large gene expression datasets from multiple tissues (liver, skeletal muscle, kidney) over time.
  • Investigating systemic temporal response cascades to therapeutic doses in the same animals.
  • Utilizing Affymetrix U34A time course gene expression data.

Purpose of the Study:

  • Identify concordance and common differentially expressed genes across tissues over time.
  • Enhance detection power for differentially expressed genes through meta-analysis.
  • Examine tissue-specific differential responses to drug treatment.

Main Methods:

  • Bayesian categorical models for initial gene pre-screening.
  • Hierarchical Bayesian Mixture Models for identifying time-varying differentially expressed genes and clusters.

Related Experiment Videos

Last Updated: Jul 2, 2026

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
09:50

Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke

Published on: February 12, 2015

  • Deviance Information Criterion for model selection and component determination.
  • Bayesian meta-inference to integrate findings across multiple tissues.

    • Main Results:

    • Identified common genes expressed across kidney, liver, and muscle tissues.
    • Observed distinct temporal regulation (up/down/no regulation) of common genes.
    • Determined differential gene expression levels: liver > kidney > muscle.

    Conclusions:

    • Commonly expressed genes across tissues can serve as potential therapeutic targets.
    • Tissue-specific responses highlight the complexity of systemic drug effects.
    • The developed Bayesian meta-analysis framework increases statistical power for detecting subtle gene expression changes.