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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...

Thermodynamic Potentials

Thermodynamic Potentials

Thermodynamic potentials are state functions that are extremely useful in analyzing a thermodynamic system. They have dimensions of energy. The four important thermodynamic potentials are internal energy, enthalpy, Helmholtz free energy, and Gibbs free energy. These thermodynamic potentials can be expressed using two of the following variables: pressure, volume, temperature, and entropy. These two variables are expressed as the rate of change of the thermodynamic potential with respect to other...

Thermodynamics: Activity Coefficient

Thermodynamics: Activity Coefficient

Activity is the measure of the effective concentration of the species in solution. It can be expressed as the product of the molar concentration of the species and its activity coefficient. The activity coefficient is a dimensionless quantity and depends on the total ionic strength of the solution.
The activity coefficient is a measure of the deviation from ideal behavior. When the ionic strength of the solution is minimal, the activity coefficient of an ionic species is close to unity, making...

Transcription Initiation

Transcription Initiation

Initiation is the first step of transcription in eukaryotes. Prokaryotic RNA Polymerase (RNAP) can bind to the template DNA and start transcribing. On the other hand, transcription in eukaryotes requires additional proteins, called transcription factors, to first bind to the promoter region in the DNA template. This binding helps recruit the specific RNAP that can assemble on the DNA and start transcription.
The promoters and enhancers and their accessory proteins allow tight regulation 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...

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...

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Related Experiment Video

Updated: Jun 30, 2026

Measuring the Kinetics of mRNA Transcription in Single Living Cells

Measuring the Kinetics of mRNA Transcription in Single Living Cells

Published on: August 25, 2011

tCal: transcriptional probability calculator using thermodynamic model.

Xin Zhou¹, Zhen Su

¹College of Biological Sciences, China Agricultural University.

Bioinformatics (Oxford, England)

|September 18, 2008

Summary

A new thermodynamic model enhances bacterial gene regulation analysis. The tCal Python module simplifies calculating transcription probabilities and building gene network models.

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Area of Science:

Systems Biology
Computational Biology
Molecular Biology

Background:

Thermodynamic models offer realistic insights into bacterial gene transcriptional regulation.
Transcription probability calculations are grounded in the physical interpretation of biological knowledge.
Existing models provide a foundation for developing more generalized approaches.

Purpose of the Study:

To extend existing thermodynamic models for bacterial gene regulation.
To develop a generalized model applicable to gene network studies.
To implement the model in an accessible Python module for researchers.

Main Methods:

Derivation of a generalized thermodynamic model for transcription probability.
Implementation of the model in a Python module named 'tCal'.
Facilitation of transcription unit construction and probability computation within the module.

Main Results:

A novel, generalized thermodynamic model for gene regulation was derived.
The 'tCal' Python module was developed for practical application.
Users can compute transcription probabilities and construct gene network models using tCal.
SBML (Systems Biology Markup Language) models of regulatory networks can be generated.

Conclusions:

The developed thermodynamic model and 'tCal' module offer a powerful tool for gene network modeling.
The module simplifies the process of analyzing bacterial gene transcriptional regulation.
This work facilitates further research in systems biology and computational biology.