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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
Cis-regulatory Sequences02:02

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...
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...
Regulation of Expression at Multiple Steps01:23

Regulation of Expression at Multiple Steps

The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the addition of a...
Cell Specific Gene Expression01:58

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...
Constitutive and Regulated Gene Expression01:27

Constitutive and Regulated Gene Expression

Gene expression in prokaryotes is governed by constitutive and regulated systems, allowing cells to balance the production of essential proteins with adaptive responses to environmental changes.Constitutive Gene ExpressionConstitutive, or housekeeping, genes are continuously expressed as they encode proteins vital for fundamental cellular processes. These include enzymes for glycolysis, ribosomal components for protein synthesis, and proteins involved in DNA replication. Their constant...

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Updated: Jun 20, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
07:23

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Computing consistency between microarray data and known gene regulation relationships.

Dong-Guk Shin1, Saira A Kazmi, Baikang Pei

  • 1Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269, USA. shin@engr.uconn.edu

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
|September 29, 2009
PubMed
Summary
This summary is machine-generated.

This study presents an automated method to compare microarray gene expression data with known gene regulation networks. This approach helps validate biological hypotheses and understand experimental context by identifying consistent regulatory relationships.

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Last Updated: Jun 20, 2026

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07:23

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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Analysis of Combinatorial miRNA Treatments to Regulate Cell Cycle and Angiogenesis
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Area of Science:

  • Bioinformatics
  • Systems Biology
  • Molecular Biology

Background:

  • Microarray experiments yield high-throughput gene expression data.
  • Biomedical literature is rich in gene regulation information.
  • Integrating these data sources is crucial for biological discovery.

Purpose of the Study:

  • To develop an automated system for comparing microarray data with known gene regulation relationships.
  • To provide a method for validating hypotheses tested in microarray experiments.
  • To facilitate rapid understanding of microarray experiment contexts.

Main Methods:

  • Introduction of a gene regulation network model.
  • Development of algorithms to isolate maximally consistent networks.
  • Extension of the model to handle multiple regulatory factors and identify inconsistencies.

Main Results:

  • Demonstration of a systematic approach to assess consistency between gene expression data and regulatory networks.
  • Identification of the peroxisome proliferator-activated receptor (PPAR) pathway as highly consistent within KEGG pathways.
  • Isolation of key regulatory relationships, including nfkb1, in macrophage response to inflammation.

Conclusions:

  • The presented method offers an effective way to compare and validate gene expression data against known biological pathways.
  • This approach aids in understanding complex gene regulatory mechanisms and experimental outcomes.
  • The findings support the utility of computational methods in advancing biological research and hypothesis testing.