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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...
Chromatin Immunoprecipitation- ChIP02:36

Chromatin Immunoprecipitation- ChIP

Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
Types of ChIP
ChIP can be divided into two types - X-ChIP and N-ChIP. X-ChIP involves in vivo cross-linking of histones and regulatory proteins to DNA, fragmenting the DNA by sonication, and isolating the protein-DNA...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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...

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Related Experiment Video

Updated: Jul 7, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
06:38

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

Published on: February 7, 2019

Asap: a framework for over-representation statistics for transcription factor binding sites.

Troels T Marstrand1, Jes Frellsen, Ida Moltke

  • 1Bioinformatics Centre, Department of Molecular Biology and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.

Plos One
|February 21, 2008
PubMed
Summary

The Asap software package efficiently detects transcription factor binding sites. Binomial over-representation and Fisher's exact test are optimal statistics for this analysis.

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

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PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins
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PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins

Published on: July 2, 2010

Related Experiment Videos

Last Updated: Jul 7, 2026

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
06:38

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

Published on: February 7, 2019

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

PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins
12:24

PAR-CliP - A Method to Identify Transcriptome-wide the Binding Sites of RNA Binding Proteins

Published on: July 2, 2010

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Efficient computational detection of over-represented transcription factor binding sites is crucial for gene regulation studies.
  • Several methods exist to test for common regulatory regimes in co-regulated genes based on transcription factor binding sites.
  • Guidance for end-users in selecting appropriate methods is limited, often requiring multiple software installations.

Purpose of the Study:

  • Introduce Asap, a software package for rapid searching with position weight matrices.
  • Compare standard methods for assessing over-representation of transcription factor binding sites.
  • Identify optimal statistical methods for detecting over-represented binding sites in artificial promoter sequences.

Main Methods:

  • Developed the Asap software package for fast position weight matrix searching.
  • Utilized artificial promoter sequences with controlled parameters for comparative analysis.
  • Evaluated multiple statistical methods for over-representation assessment across various thresholds and sequence set distributions.

Main Results:

  • Asap demonstrates significantly faster performance compared to naive scanning algorithms for large datasets and numerous weight matrices.
  • Binomial over-representation and Fisher's exact test were identified as the best-performing statistics.
  • These optimal statistics outperformed other tested methods in detecting over-represented transcription factor binding sites.

Conclusions:

  • Asap provides a computationally efficient solution for identifying transcription factor binding sites.
  • Binomial over-representation and Fisher's exact test are recommended for robust over-representation analysis.
  • An accessible online server for Asap is available to facilitate research.