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Related Concept Videos

General Transcription Factors01:30

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...
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...
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...
Combinatorial Gene Control02:33

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...
RNA Polymerase II Accessory Proteins02:36

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...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: May 11, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
09:58

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Identifying context-specific transcription factor targets from prior knowledge and gene expression data.

Elana J Fertig1, Alexander V Favorov, Michael F Ochs

  • 1Department of Oncology, SKCCC, School of Medicine, Johns Hopkins University, Baltimore, MD 21218, USA. ejfertig@jhmi.edu

IEEE Transactions on Nanobioscience
|May 23, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new statistic to identify context-specific transcription factor (TF) targets, improving accuracy in gene expression analysis. The method refines TF target identification, particularly for cell signaling in gastrointestinal stromal tumors (GIST).

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Transcription factors (TFs) rarely regulate targets universally; context-specific activation alters transcriptional responses.
  • Inferring TF targets from gene expression data is complex due to multifactorial regulation in mammalian genes.

Purpose of the Study:

  • To present a novel statistic for inferring context-specific TF regulation.
  • To enhance the accuracy of TF target identification using gene expression data.

Main Methods:

  • Developed a novel statistic based on the CoGAPS algorithm.
  • Utilized simulated data for numerical experiments to validate the statistic's performance.
  • Applied the statistic to refine TF targets relevant to cell signaling in gastrointestinal stromal tumors (GIST).

Main Results:

  • The statistic correctly inferred common TF targets, showing robustness to moderate error levels.
  • It identified fewer false positives than false negatives in simulated datasets.
  • Significantly refined TF targets for GIST cell signaling, aligning with known TF phosphorylation patterns.

Conclusions:

  • The novel statistic accurately infers context-specific TF regulation.
  • It offers wide applicability for inferring set membership in integrated biological datasets.
  • The method can be extended to incorporate prior probabilities or additional candidate gene targets.