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DNA Microarrays

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...

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Related Experiment Video

Updated: May 31, 2026

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Published on: November 11, 2014

Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis.

Franc Llorens¹, Manuela Hummel, Xavier Pastor

¹Center for Genomic Regulation (CRG)-Universitat Pompeu Fabra (UPF), Barcelona, Spain.

|June 25, 2011

Summary

This study combined microarray and digital gene expression profiling to identify genes regulated by Epidermal Growth Factor (EGF). The findings reveal new genes involved in EGF signaling and validate a robust gene set for cancer research.

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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis

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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform

Published on: August 10, 2009

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Epidermal Growth Factor (EGF) regulates critical cellular processes including proliferation and survival.
EGF signaling is implicated in both normal development and various diseases, notably cancer.

Purpose of the Study:

To comprehensively analyze the Epidermal Growth Factor (EGF) dependent transcriptome in HeLa cells.
To identify novel genes and pathways influenced by EGF signaling.

Main Methods:

Utilized a combined approach of multiple microarray platforms (Agilent, Operon, Illumina) and digital gene expression profiling (DGE) via Illumina Genome Analyzer.
Applied cross-platform data meta-analysis using RankProd and GlobalAncova statistical tests.

Main Results:

Established a well-validated gene set with altered transcript levels following EGF treatment.
Constructed higher-order gene interaction networks, reinforcing the role of EGF signaling in cancer.
Identified a novel set of genes not previously associated with known EGF functions.

Conclusions:

Global genomic cross-validation from high-content technologies yields more reliable datasets.
This approach enhances confidence in downstream in silico functional inference analyses.