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Related Concept Videos

Transcription Factors02:16

Transcription Factors

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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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General Transcription Factors01:30

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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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Gene transcription is regulated by the synergistic action of several proteins that form a complex at a gene regulatory site. This is observed in eukaryotes, where the regulation of gene expression is a complex process. Regulatory proteins in eukaryotes can broadly be classified into two types – regulators that bind directly to specific DNA sequences and co-regulators that associate with regulatory proteins but cannot directly bind to the DNA. These co-regulators are further divided into...
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Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...
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Identifying transcription factor complexes and their roles.

Thorsten Will1, Volkhard Helms1

  • 1Center for Bioinformatics, Campus Building E2.1, Saarland University, D-66123 Saarbrücken, Germany.

Bioinformatics (Oxford, England)
|August 28, 2014
PubMed
Summary

We developed DACO, a novel algorithm for predicting protein complexes. DACO integrates protein-protein and domain-domain interactions, outperforming existing methods in identifying transcription factor complexes and their regulatory roles.

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Area of Science:

  • Computational biology
  • Systems biology
  • Bioinformatics

Background:

  • Eukaryotic gene expression relies on complex molecular logic circuits integrating regulatory signals.
  • Transcription factor (TF) complexation is a conserved mechanism for signal integration in regulatory pathways.
  • Existing protein complex prediction methods struggle with dynamic, combinatorial assemblies.

Purpose of the Study:

  • To develop a novel algorithm for predicting dynamic, combinatorial protein complexes.
  • To improve the accuracy of identifying transcription factor complexes and their regulatory functions.

Main Methods:

  • Developed the DACO algorithm, integrating protein-protein and domain-domain interaction networks.
  • Utilized the cohesiveness metric to optimize cluster quality at the protein interaction level.
  • Applied connectivity constraints at the domain level to capture combinatorial interactions.

Main Results:

  • DACO significantly outperformed popular complex prediction methods in identifying TF complexes in Saccharomyces cerevisiae.
  • Successfully assigned many predicted complexes to target genes and inferred regulatory effects consistent with literature.
  • Demonstrated the algorithm's capability to reveal dynamic, combinatorial assemblies.

Conclusions:

  • DACO offers a powerful new approach for predicting dynamic protein complexes.
  • The algorithm enhances understanding of gene regulation by identifying TF complexes and their functions.
  • DACO provides a valuable tool for systems biology research.