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Related Concept Videos

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...
RNA Polymerase II Accessory Proteins02:36

RNA Polymerase II Accessory Proteins

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...
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...
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...
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...

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Related Experiment Video

Updated: May 20, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Ab initio prediction of transcription factor targets using structural knowledge.

Tommy Kaplan1, Nir Friedman, Hanah Margalit

  • 1School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel.

Plos Computational Biology
|August 17, 2005
PubMed
Summary

This study introduces a novel structure-based method to identify transcription factor binding sites without prior gene data. The approach predicts binding sites for new proteins, enabling functional inference for Drosophila melanogaster transcription factors.

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Last Updated: May 20, 2026

A Protocol for Computer-Based Protein Structure and Function Prediction
16:41

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
12:54

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Published on: March 7, 2018

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
09:58

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Area of Science:

  • Genomics
  • Structural Biology
  • Bioinformatics

Background:

  • Transcription factor binding site identification typically requires extensive known target gene data.
  • Novel transcription factors often lack sufficient binding data for accurate site identification.

Purpose of the Study:

  • To develop a novel structure-based approach for predicting transcription factor binding sites.
  • To enable the identification of binding sites for transcription factors with no prior binding data.
  • To infer the function and activity of transcription factors using predicted binding sites and associated data.

Main Methods:

  • Combining sequence and structural data to infer amino acid-nucleotide recognition preferences.
  • Predicting binding sites for novel transcription factors within the same structural family.
  • Applying the method to the Cys(2)His(2) Zinc Finger protein family.
  • Performing genome-wide scans for direct targets of Drosophila melanogaster Cys(2)His(2) transcription factors.

Main Results:

  • The developed approach successfully predicts DNA-recognition preferences compatible with experimental results.
  • Genome-wide prediction of direct targets for Drosophila melanogaster Cys(2)His(2) transcription factors was achieved.
  • Analysis of predicted targets, gene annotation, and expression data allowed for functional inference.

Conclusions:

  • The novel structure-based method provides a powerful tool for identifying transcription factor binding sites, especially for previously uncharacterized factors.
  • This approach facilitates the discovery of direct gene targets and aids in inferring the functional roles of transcription factors.
  • The method is particularly valuable for studying transcription factors like the Cys(2)His(2) Zinc Finger family and their roles in organisms such as Drosophila melanogaster.