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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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Updated: Jun 26, 2026

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

High-Density DNA and RNA microarrays - Photolithographic Synthesis, Hybridization and Preparation of Large Nucleic Acid Libraries

Published on: August 12, 2019

Compressive sensing DNA microarrays.

Wei Dai¹, Mona A Sheikh, Olgica Milenkovic

¹Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.

EURASIP Journal on Bioinformatics & Systems Biology

|January 23, 2009

Summary

This summary is machine-generated.

Compressive sensing microarrays (CSMs) offer efficient DNA detection by enabling sensors to identify multiple targets. This research develops new probe design and signal recovery methods for accurate hybridization profiling, even with short assay times.

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Last Updated: Jun 26, 2026

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Published on: August 12, 2019

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Published on: November 15, 2017

Area of Science:

Biotechnology
Genomics
Signal Processing

Background:

Conventional DNA microarrays detect single targets per sensor.
Compressive sensing microarrays (CSMs) utilize group testing and compressive sensing (CS) for multiplexed detection.
Designing CSMs requires integrating CS theory with DNA hybridization biochemistry.

Purpose of the Study:

To develop methods for designing CSMs that balance CS constraints with DNA hybridization realities.
To propose a cross-hybridization model for CSMs.
To create probe design and CS signal recovery techniques based on this model.

Main Methods:

Development of a novel cross-hybridization model for CSMs.
Implementation of probe design strategies tailored to the model.
Application of CS signal recovery algorithms adapted for CSM data.
Laboratory experiments to validate the proposed methods.

Main Results:

Consensus probe sequences need at least 80% homology with target DNA for accurate hybridization profiling.
Out-of-equilibrium hybridization data yield accuracy comparable to equilibrium conditions.
The developed methods enable accurate detection using CSMs.

Conclusions:

CSMs can be effectively designed by considering both CS principles and DNA hybridization characteristics.
Accurate CSMs can be achieved with specific probe design criteria and signal recovery techniques.
The efficiency of CSMs allows for applications with limited hybridization times.