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Related Concept Videos

Master Transcription Regulators02:23

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...
Master Transcription Regulators02:23

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...
Bacterial Transcription01:53

Bacterial Transcription

RNA polymerase (RNAP) carries out DNA-dependent RNA synthesis in both bacteria and eukaryotes. Bacteria do not have a membrane-bound nucleus. So, transcription and translation occur simultaneously, on the same DNA template.
Transcription can be divided into three main stages, each involving distinct DNA sequences to guide the polymerase. These are:
Transcription01:17

Transcription

Transcription is the synthesis of RNA from a DNA sequence by RNA polymerase. It is the first step in producing a protein from a gene sequence. Additionally, many other proteins and regulatory sequences are involved in correctly synthesizing messenger RNA (mRNA). Transcriptional regulation is responsible for the differentiation of different types of cells and often for the proper cellular response to environmental signals.
Transcription Can Produce Different Kinds of RNA Molecules
In eukaryotes,...
Transcription Attenuation in Prokaryotes02:42

Transcription Attenuation in Prokaryotes

Transcriptional attenuation occurs when RNA transcription is prematurely terminated due to the formation of a terminator mRNA hairpin structure.  Bacteria use these hairpins to regulate the transcription process and control the synthesis of several amino acids including histidine, lysine, threonine, and phenylalanine. Transcription attenuation takes place in the non-coding regions of mRNA.
There are several different mechanisms used to attenuate transcription. In ribosome mediated...
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: Jun 2, 2026

DNA-Tethered RNA Polymerase for Programmable In vitro Transcription and Molecular Computation
09:26

DNA-Tethered RNA Polymerase for Programmable In vitro Transcription and Molecular Computation

Published on: December 29, 2021

An Iterative Time Windowed Signature Algorithm for Time Dependent Transcription Module Discovery.

Jia Meng1, Shou-Jiang Gao, Yufei Huang

  • 1Dept. of ECE, University of Texas at San Antonio San Antonio, TX 78249.

IEEE International Workshop on Genomic Signal Processing and Statistics : [Proceedings]. IEEE International Workshop on Genomic Signal Processing and Statistics
|May 10, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel algorithm to identify time-varying gene expression modules and their timing from large-scale data. This approach enhances understanding of dynamic biological processes beyond static module discovery.

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Analysis of Termination of Transcription Using BrUTP-strand-specific Transcription Run-on (TRO) Approach
12:12

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In Vitro Transcription Assays and Their Application in Drug Discovery
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In Vitro Transcription Assays and Their Application in Drug Discovery

Published on: September 20, 2016

Area of Science:

  • Genomics
  • Computational Biology
  • Systems Biology

Background:

  • Existing methods often assume static transcription modules, failing to capture dynamic gene regulation over time.
  • Understanding temporal gene regulation is crucial for deciphering complex biological processes.

Purpose of the Study:

  • To develop an algorithm for discovering time-varying gene modules and their temporal activity from genome-wide expression data.
  • To provide a rigorous mathematical framework for defining and retrieving time-dependent transcription modules (TDTMs).

Main Methods:

  • Proposed a novel algorithm to discover time-varying modules and their timing information from time-series gene expression data.
  • Defined time-dependent transcription modules (TDTMs) as sets of co-regulated genes during specific time intervals.
  • Utilized an iterative signature algorithm based on the TDTM mathematical definition to retrieve modules.

Main Results:

  • Successfully identified time-varying transcription modules and their temporal activity from simulated and real biological data.
  • Demonstrated the algorithm's capability to capture dynamic gene regulation patterns.
  • Validated findings using human time-series microarray data during KSHV infection and Expression Analysis Systematic Explorer.

Conclusions:

  • The developed algorithm effectively discovers time-varying gene modules and their temporal dynamics, offering a significant advancement over static approaches.
  • This method provides valuable insights into the timing of gene regulation, crucial for understanding dynamic biological systems.
  • The TDTM framework offers a robust approach for analyzing temporal gene expression data.