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Transcription Factors

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 Factors

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...

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...

Combinatorial Gene Control

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...

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...

RNA Polymerase II Accessory Proteins

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...

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Related Experiment Video

Updated: May 26, 2026

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Generating the Transcriptional Regulation View of Transcriptomic Features for Prediction Task and Dark Biomarker Detection on Small Datasets

Published on: March 1, 2024

Bayesian non-negative factor analysis for reconstructing transcription factor mediated regulatory networks.

Jia Meng¹, Jianqiu Michelle Zhang, Yidong Chen

¹Department of Electrical and Computer Engineering, University of Texas at San Antonio, San Antonio, Texas, USA. yhuang@utsa.edu.

Proteome Science

|December 15, 2011

Summary

This study introduces a new Bayesian model to reconstruct transcriptional regulatory networks. The method accurately identifies transcription factor activities and improves sample clustering for biological data analysis.

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Identification of Transcription Factor Regulators using Medium-Throughput Screening of Arrayed Libraries and a Dual-Luciferase-Based Reporter

Identification of Transcription Factor Regulators using Medium-Throughput Screening of Arrayed Libraries and a Dual-Luciferase-Based Reporter

Published on: March 27, 2020

Area of Science:

Computational Biology
Systems Biology
Genomics

Background:

Transcriptional regulation by transcription factors (TFs) governs gene expression timing and mRNA abundance.
Limitations in current proteomics hinder large-scale measurement of TF activities, complicating computational reconstruction of regulatory networks.

Purpose of the Study:

To develop a novel computational approach for reconstructing transcription factor-mediated regulatory networks.
To simultaneously infer network structure, regulatory coefficients, and TF activities.

Main Methods:

A Bayesian non-negative factor model incorporating Dirichlet process mixtures and sparse distributions was proposed.
A Gibbs sampling solution was developed for simultaneous inference of network structure and TF activities.
The model integrates prior knowledge from databases to constrain sparsity.

Main Results:

The method successfully reconstructed TF-mediated transcriptional regulatory network structures and TF activities from simulated and real breast cancer data.
Accurate prediction of regulatory targets and superior sample clustering performance compared to existing methods were achieved.
The model effectively identified TF protein level activities and sample clustering effects.

Conclusions:

The proposed Bayesian approach demonstrates validity and effectiveness in reconstructing TF-mediated transcriptional networks.
The method offers a robust tool for analyzing gene expression data and understanding regulatory mechanisms.