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Related Concept Videos

Transcription Factors02:16

Transcription Factors

82.8K
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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Transcription Elongation Factors02:35

Transcription Elongation Factors

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Transcription elongation is a dynamic process that alters depending upon the sequence heterogeneity of the DNA being transcribed. Hence, it is not surprising that the elongation complex's composition also varies along the way while transcribing a gene.
The transcription elongation is regulated via pausing of RNA polymerase on several occasions during transcription. In bacteria, these halts are necessary because the transcription of DNA into mRNA is coupled to the translation of that mRNA...
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Transcription Elongation Factors02:35

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Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

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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...
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General Transcription Factors01:30

General 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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Related Experiment Video

Updated: Feb 6, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
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High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Published on: February 7, 2019

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Disentangling transcription factor binding site complexity.

Ralf Eggeling1

  • 1Department of Computer Science, University of Helsinki, Gustaf-Hällströmin katu 2b, FIN-00140 Helsinki, Finland.

Nucleic Acids Research
|August 8, 2018
PubMed
Summary
This summary is machine-generated.

This study distinguishes transcription factor (TF) binding motif complexity from co-binding TF interference using statistical analysis. It suggests intra-motif dependencies may be overestimated in in vivo data.

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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

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Related Experiment Videos

Last Updated: Feb 6, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
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Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Transcription factor (TF) binding motifs often exhibit complexity beyond simple models.
  • Existing methods for modeling TF motif complexity (dependencies, heterogeneities) have limitations with in vivo data due to potential interference from co-binding factors.

Purpose of the Study:

  • To develop a method for distinguishing intrinsic TF motif complexity from artifacts caused by co-binding factors.
  • To investigate whether intra-motif complexity is better represented by dependencies, heterogeneities, or variants.

Main Methods:

  • Statistical analysis of TF binding site properties to differentiate motif complexity types.
  • Benchmarking of methods for motif discovery and artifact correction.

Main Results:

  • Successfully distinguished intra-motif complexity from inter-motif interference using statistical properties.
  • Demonstrated the effectiveness of methods in detecting and correcting artifacts in motif discovery.
  • Identified that intra-motif dependencies might be overestimated in previous in vivo studies.

Conclusions:

  • The developed statistical approach effectively separates different sources of TF motif complexity.
  • Reassessment of the prevalence of intra-motif dependencies in in vivo TF binding is warranted.
  • Improved motif discovery tools can mitigate artifacts arising from complex binding scenarios.