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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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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

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Bioinformatics and Microarray Data Analysis on the Cloud.

Barbara Calabrese¹, Mario Cannataro²

¹Department of Medical and Surgical Sciences, University Magna Graecia of Catanzaro, 88100, Catanzaro, Italy.

Methods in Molecular Biology (Clifton, N.J.)

|April 13, 2015

Summary

This summary is machine-generated.

Cloud computing offers scalable solutions for managing large omics datasets from high-throughput platforms. However, data security and privacy challenges persist, especially for sensitive patient data in personalized medicine.

Keywords:

Bioinformatics Cloud computing Microarray data analysis

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

High-throughput omics platforms (microarray, mass spectrometry, next-generation sequencing) generate vast datasets requiring significant storage and computational resources.
Cloud computing provides scalable storage, computing power, and accessibility, making it a promising technology for bioinformatics.
The adoption of cloud-based bioinformatics solutions is increasing in both academic and industrial settings.

Purpose of the Study:

To review academic and industrial cloud-based bioinformatics solutions.
To focus specifically on cloud solutions for microarray data analysis.
To highlight key challenges and issues concerning the use of cloud platforms for patient data storage and analysis.

Main Methods:

Literature review of academic and industrial cloud-based bioinformatics solutions.
Analysis of cloud platform capabilities for omics data storage and computation.
Examination of security and privacy concerns related to patient data in cloud environments.

Main Results:

Several cloud-based bioinformatics solutions are available for omics data analysis.
Cloud platforms offer scalable resources but present security and privacy challenges.
Microarray data analysis solutions are a notable area of cloud adoption.

Conclusions:

Cloud computing is a key technology for handling large-scale omics data.
Addressing security and privacy concerns is crucial for cloud-based analysis of patient data, particularly in personalized medicine.
Further development and standardization are needed for secure and efficient cloud bioinformatics solutions.