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Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

Cis-regulatory Sequences

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

Cis-regulatory Sequences

Cis-regulatory Sequences

General Transcription Factors

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...

Cell Specific Gene Expression

Cell Specific Gene Expression

Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

Cell Specific Gene Expression

Cell Specific Gene Expression

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Related Experiment Video

Updated: Jan 10, 2026

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

Motif-based models accurately predict cell type-specific distal regulatory elements.

Paola Cornejo-Páramo^1,2, Xuan Zhang¹, Lithin Louis¹

¹Victor Chang Cardiac Research Institute, Darlinghurst, NSW, Australia.

Nature Communications

|November 24, 2025

Summary

We developed Bag-of-Motifs (BOM), a simple yet powerful computational framework. BOM accurately predicts cell-type-specific enhancers by analyzing transcription factor (TF) motifs, outperforming complex models.

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Last Updated: Jan 10, 2026

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Area of Science:

Genomics
Computational Biology
Molecular Biology

Background:

Understanding how DNA sequence dictates cell-specific gene regulation is crucial.
Distal cis-regulatory elements control gene expression but their sequence code is complex.

Purpose of the Study:

To present Bag-of-Motifs (BOM), a novel computational framework for predicting cell-type-specific enhancers.
To demonstrate BOM's accuracy and interpretability across diverse species.

Main Methods:

Representing cis-regulatory elements as unordered counts of transcription factor (TF) motifs.
Utilizing gradient-boosted trees for predictive modeling.
Validating predictions through experimental construction of synthetic enhancers.

Main Results:

BOM accurately predicts cell-type-specific enhancers in mouse, human, zebrafish, and Arabidopsis.
BOM outperforms complex deep-learning models in prediction accuracy with fewer parameters.
Experimental validation confirmed that predicted motif sets drive cell-type-specific expression.

Conclusions:

BOM provides a scalable and interpretable framework for dissecting cis-regulatory grammar.
A simple sequence code within distal regulatory regions drives cell-type-specific gene activity.
BOM offers broad applicability for gene regulation studies across species.