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Related Experiment Video

Updated: Mar 15, 2026

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions
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"Upstream Analysis": An Integrated Promoter-Pathway Analysis Approach to Causal Interpretation of Microarray Data.

Jeannette Koschmann1, Anirban Bhar2, Philip Stegmaier3

  • 1Xplain GmbH, D-38302 Wolfenbüttel, Germany. jeannette.koschmann@genexplain.com.

Microarrays (Basel, Switzerland)
|September 8, 2016
PubMed
Summary

This study introduces a novel bioinformatic workflow to identify master regulators controlling co-expressed genes. The method successfully pinpointed tissue-specific regulators linked to cancer and apoptosis in mouse liver and lung tissues.

Keywords:
gene expression signaturesmicroarray datapathway analysispromoter analysisupstream analysis

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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Genomics

Background:

  • Co-expressed genes often share common regulatory influences, complicating causal analysis.
  • Identifying upstream regulators of gene expression is crucial for understanding biological processes.
  • Existing methods may not fully capture complex regulatory networks.

Purpose of the Study:

  • To develop and validate a computational strategy for causal analysis of co-expressed genes.
  • To identify hypothetical master regulators by integrating promoter analysis with upstream pathway knowledge.
  • To apply this strategy to gene expression data from naphthalene-induced murine liver and lung tissues.

Main Methods:

  • A workflow combining state-of-the-art promoter analysis for transcription factor (TF) binding sites.
  • Knowledge-based analysis of upstream pathways controlling TF activity.
  • Application of a novel triclustering algorithm to gene expression signatures.
  • Implementation within a comprehensive bioinformatic software platform.

Main Results:

  • Identification of hypothetical master regulators controlling co-expressed genes.
  • Successful application to gene sets from naphthalene-induced murine liver and lung tissues.
  • Discovery of tissue-specific master regulators associated with tumorigenic and apoptotic processes.

Conclusions:

  • The presented strategy enables causal analysis of co-expressed genes by identifying master regulators.
  • This is the first reported use of gene expression triclusters to identify upstream regulators.
  • The workflow provides a powerful tool for dissecting regulatory networks in various biological contexts.