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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: Apr 25, 2026

Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Extracellular Protein Microarray Technology for High Throughput Detection of Low Affinity Receptor-Ligand Interactions

Published on: January 7, 2019

Microarray R-based analysis of complex lysate experiments with MIRACLE.

Markus List¹, Ines Block², Marlene Lemvig Pedersen²

¹Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark Lundbeckfonden Center of Excellence in Nanomedicine NanoCAN, Molecular Oncology, Institute of Molecular Medicine, Human Genetics, Institute of Clinical Research, Epidemiology, Biostatistics and Biodemography, Institute of Public Health and Department of Mathematics and Computer Science, University of Southern Denmark, 5000 Odense, Denmark.

Bioinformatics (Oxford, England)

|August 28, 2014

Summary

This summary is machine-generated.

MIRACLE is a web application that simplifies sample management and data analysis for reverse-phase protein arrays (RPPAs). It provides an end-to-end solution, enhancing the utility of RPPA technology for high-throughput protein quantification.

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Area of Science:

Biochemistry
Proteomics
Bioinformatics

Background:

Reverse-phase protein arrays (RPPAs) enable high-throughput protein quantification but face challenges in sample management and data analysis.
Effective integration of sample tracking and data processing is crucial for RPPA technology utilization.
Existing RPPA workflows often neglect comprehensive sample management strategies.

Purpose of the Study:

To develop MIRACLE, a user-friendly web application for integrated sample management and data analysis in RPPA experiments.
To provide an end-to-end solution for researchers utilizing RPPA technology.
To facilitate the broader adoption of RPPA for high-throughput protein analysis.

Main Methods:

Development of a comprehensive web application (MIRACLE) for RPPA sample tracking.
Implementation of data processing pipelines including staining bias correction and normalization.
Integration of established statistical analysis methods and R data export functionality.

Main Results:

MIRACLE offers a user-friendly interface for managing sample information throughout the RPPA workflow.
The application provides automated data processing, including normalization and statistical evaluation.
MIRACLE supports both integrated analysis and data export for advanced R-based analyses.

Conclusions:

MIRACLE addresses the neglected aspect of sample management in RPPA, offering an end-to-end solution.
The application enhances the utility and accessibility of RPPA technology for experimental scientists.
MIRACLE has the potential to increase the widespread adoption of RPPA for high-throughput proteomics research.