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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...
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...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Proteomics01:33

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term proteomics...
MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...

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Updated: Jun 26, 2026

Performing Custom MicroRNA Microarray Experiments
07:04

Performing Custom MicroRNA Microarray Experiments

Published on: October 28, 2011

Overview of mRNA expression profiling using DNA microarrays.

Fumiaki Katagiri1, Jane Glazebrook

  • 1University of Minnesota, St. Paul, Minnesota, USA.

Current Protocols in Molecular Biology
|January 27, 2009
PubMed
Summary

DNA microarray technology measures thousands of genes simultaneously. Careful experimental design and statistical analysis are crucial for interpreting large microarray datasets in molecular biology research.

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Last Updated: Jun 26, 2026

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Published on: December 3, 2010

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • DNA microarray technology enables high-throughput measurement of gene expression.
  • Large-scale genomic data present significant experimental design and statistical analysis challenges.
  • Molecular biologists often require guidance on applying these advanced techniques.

Purpose of the Study:

  • To provide an overview of DNA microarray technology applications.
  • To discuss challenges in experimental design and statistical analysis for microarray data.
  • To guide investigators in choosing appropriate methods based on scientific goals.

Main Methods:

  • Discussion of various microarray experimental designs.
  • Review of statistical approaches for analyzing large-scale gene expression data.
  • Evaluation of the merits and limitations of different microarray methods.

Main Results:

  • Identified key factors influencing microarray experiment success: array type, experimental design, replication, and statistical analysis.
  • Highlighted the importance of aligning methodological choices with specific research questions.
  • Provided insights into the trade-offs associated with different microarray analysis strategies.

Conclusions:

  • Effective utilization of DNA microarray technology requires careful consideration of experimental and analytical methodologies.
  • Tailoring experimental design and statistical analysis to research objectives is essential for robust biological insights.
  • This overview aims to equip molecular biologists with the knowledge to navigate the complexities of microarray data analysis.