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ChEA-KG: Human Transcription Factor Regulatory Network with a Knowledge Graph Interactive User Interface.

Anna I Byrd1, John Erol Evangelista1, Alexander Lachmann1

  • 1Department of Pharmacological Sciences, Department of Artificial Intelligence and Human Health, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

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|August 20, 2025
PubMed
Summary
This summary is machine-generated.

Researchers constructed a high-quality human gene regulatory network (GRN) by analyzing transcription factor (TF) enrichment. This GRN maps TF connections and aids in understanding gene expression regulation and TF roles in cell types and cancers.

Keywords:
Cancer subtypesCell typesEnrichment analysisGene regulatory networkKnowledge graphLung Squamous Cell CarcinomaNetwork visualizationTranscription factor

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Gene expression is regulated by transcription factors (TFs) that bind DNA.
  • TFs form complex gene regulatory networks (GRNs) with intricate feedback loops.
  • Existing methods for reconstructing human GRNs are often experimental or computational.

Purpose of the Study:

  • To develop a novel computational approach for constructing a high-quality human GRN.
  • To create a comprehensive map of signed and directed edges connecting TFs.
  • To provide an interactive platform for exploring the human GRN and TF functions.

Main Methods:

  • Utilized transcription factor enrichment analysis (ChEA3) on thousands of gene sets from the RummaGEO resource.
  • Distilled signed and directed edges connecting human TFs to build the GRN.
  • Developed the ChEA-KG web server application for network visualization and analysis.

Main Results:

  • Constructed a human GRN with 131,581 signed and directed edges.
  • The GRN connects 701 source TF nodes to 1,559 target TF nodes.
  • Generated cell-type and cancer TF atlases by extending enrichment analysis.

Conclusions:

  • ChEA-KG offers a new interactive method for exploring the human GRN.
  • The application facilitates network visualization and TF enrichment analysis.
  • ChEA-KG provides valuable insights into TF regulation across human cell types and cancers.