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Related Concept Videos

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...
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...
Co-activators and Co-repressors02:04

Co-activators and Co-repressors

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...
Co-activators and Co-repressors02:04

Co-activators and Co-repressors

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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Related Experiment Video

Updated: Jun 26, 2026

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis
12:29

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Published on: April 16, 2018

Pseudocounts for transcription factor binding sites.

Keishin Nishida1, Martin C Frith, Kenta Nakai

  • 1Department of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan.

Nucleic Acids Research
|December 25, 2008
PubMed
Summary
This summary is machine-generated.

Determining the optimal pseudocount value for position weight matrices (PWMs) is crucial for accurately representing transcription factor binding sites. This study suggests a practical pseudocount value of 0.8, especially for less conserved binding sites.

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Last Updated: Jun 26, 2026

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis
12:29

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Published on: April 16, 2018

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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

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Position Weight Matrices (PWMs) are standard for representing transcription factor sequence specificity.
  • Estimating PWMs from limited binding site data introduces bias, often mitigated by pseudocounts.
  • Optimal pseudocount values remain undefined, leading to variability in PWM accuracy.

Purpose of the Study:

  • To determine optimal pseudocount values for position weight matrices (PWMs).
  • To investigate the relationship between pseudocounts, sample size, and PWM conservation.
  • To propose a practical pseudocount value for general use.

Main Methods:

  • Simulated binding site generation based on public PWM databases.
  • Comparison of generated matrices with added pseudocounts against original frequency matrices.
  • Evaluation using multiple quantitative measures to assess matrix accuracy.

Main Results:

  • Optimal pseudocount values were identifiable for many matrices, independent of sample size.
  • Optimal pseudocount values strongly correlated with the entropy of the original PWMs.
  • Higher pseudocount values are recommended for PWMs with lower sequence conservation (higher entropy).

Conclusions:

  • A pseudocount value of 0.8 is proposed as a practical, generalizable recommendation.
  • The findings provide a data-driven approach to improve the accuracy of transcription factor binding site predictions.
  • This study contributes to more reliable analyses of gene regulation through improved PWM construction.