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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...

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Related Experiment Video

Updated: May 21, 2026

Fabrication and Use of MicroEnvironment microArrays (MEArrays)
11:57

Fabrication and Use of MicroEnvironment microArrays (MEArrays)

Published on: October 11, 2012

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data

Yilin Dai1, Ling Guo, Meng Li

  • 1Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49934, USA.

BMC Research Notes
|June 12, 2012
PubMed
Summary
This summary is machine-generated.

Microarray Я US provides a user-friendly interface for R-based microarray analysis, enabling accurate results without R programming knowledge. This tool streamlines differential expression analysis and expedites functional interpretation for researchers.

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Microarray Analysis for Saccharomyces cerevisiae
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Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

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Last Updated: May 21, 2026

Fabrication and Use of MicroEnvironment microArrays (MEArrays)
11:57

Fabrication and Use of MicroEnvironment microArrays (MEArrays)

Published on: October 11, 2012

Microarray Analysis for Saccharomyces cerevisiae
13:17

Microarray Analysis for Saccharomyces cerevisiae

Published on: April 7, 2011

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Microarray data analysis is challenging for researchers lacking R programming skills.
  • Existing graphical user interfaces (GUIs) for Bioconductor lack comprehensive solutions for data accuracy and reliability.
  • There is a need for tools that simplify microarray data analysis and expedite functional analysis.

Purpose of the Study:

  • To develop an R-based GUI for Bioconductor packages to simplify microarray data analysis.
  • To address accuracy and reliability issues in microarray data analysis, particularly probe design problems.
  • To expedite the functional analysis of microarray results.

Main Methods:

  • Developed Microarray Я US, an R-based GUI implementing over a dozen Bioconductor packages.
  • Incorporated custom probe re-definition and re-annotation for Affymetrix and Illumina chips.
  • Implemented a versatile output utility for generating input files for functional analysis software.

Main Results:

  • Microarray Я US offers a streamlined workflow for differential microarray expression analysis without R knowledge.
  • The tool enhances accuracy and reliability through custom probe re-annotation.
  • A utility tool facilitates rapid generation of input files for over 20 functional analysis programs.

Conclusions:

  • Microarray Я US empowers researchers without R knowledge to perform advanced microarray analysis.
  • The software ensures more reliable and accurate microarray data analysis.
  • It significantly expedites downstream functional analysis of microarray results.