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Related Concept Videos

Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Transcription Factors02:16

Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
Transcription Factors02:16

Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
General Transcription Factors01:30

General Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...

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Related Experiment Video

Updated: May 15, 2026

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets
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Published on: March 1, 2024

Using graph models to find transcription factor modules: the hitting set problem and an exact algorithm.

Songjian Lu1, Xinghua Lu

  • 1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15219, USA. songjian@pitt.edu.

Algorithms for Molecular Biology : AMB
|January 18, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel graph-based method to identify cooperative transcription factor (TF) modules involved in gene expression regulation. The approach effectively uncovers context-specific TF modules from systems biology data.

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Last Updated: May 15, 2026

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Area of Science:

  • Systems biology
  • Molecular biology
  • Computational biology

Background:

  • Understanding signal transduction pathways is crucial for deciphering gene expression regulation.
  • Identifying transcription factors (TFs) that mediate these signals is a key challenge in systems biology.

Purpose of the Study:

  • To develop a computational method for identifying modules of cooperative transcription factors.
  • To uncover context-specific and reusable TF modules from gene expression data.

Main Methods:

  • A graph algorithm was developed to find minimum sets of cooperative TFs covering differentially expressed genes under perturbations.
  • A clique-finding approach was employed to identify TF modules consistently cooperating across various experimental conditions.

Main Results:

  • The developed method successfully identified known TF modules from individual experiments.
  • The approach demonstrated the ability to detect context-specific and frequently reused TF modules.

Conclusions:

  • The novel graph-based method provides an effective strategy for identifying transcription factor modules.
  • This approach enhances the understanding of signal transduction in gene expression systems by revealing cooperative TF behavior.