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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...
What is Gene Expression?01:42

What is Gene Expression?

Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
What is Gene Expression?01:36

What is Gene Expression?

A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then processed and...
What is Gene Expression?01:42

What is Gene Expression?

Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...

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Related Experiment Video

Updated: Jul 5, 2026

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress
05:22

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Analysis of expression data: an overview.

Anoop Grewal1, Peter Lambert, Jordan Stockton

  • 1NextBio, Cupertino, California, USA.

Current Protocols in Human Genetics
|April 23, 2008
PubMed
Summary
This summary is machine-generated.

This overview covers microarray data analysis, focusing on interpretation techniques. It explains the two main steps: data acquisition/normalization and data interpretation for microarray experiments.

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Area of Science:

  • Molecular Biology
  • Bioinformatics

Background:

  • Microarray technology enables high-throughput gene expression profiling.
  • Analyzing microarray data is crucial for understanding biological processes.

Purpose of the Study:

  • To provide an overview of microarray data analysis techniques.
  • To focus on the interpretation phase of microarray data analysis.

Main Methods:

  • Introduction to microarray chips and experimental design.
  • Discussion of data acquisition and normalization.
  • Detailed examination of data interpretation methods.

Main Results:

  • Microarray data analysis comprises data acquisition/normalization and interpretation.
  • Interpretation methods are emphasized as they are less technology-specific.

Conclusions:

  • Effective interpretation of microarray data is key to extracting biological insights.
  • Understanding analysis techniques enhances the utility of microarray experiments.