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Bioinformatics on the cloud computing platform Azure.

Hugh P Shanahan1, Anne M Owen2, Andrew P Harrison3

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Microsoft Azure cloud computing offers a scalable platform for bioinformatics, particularly for analyzing large microarray expression datasets. While the Platform as a Service (PaaS) has a learning curve, it simplifies parallel software deployment for stable bioinformatics tools.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Cloud Computing

Background:

  • Bioinformatics research increasingly requires robust computational infrastructure.
  • Analyzing large-scale biological datasets, such as microarray expression data, presents significant computational challenges.
  • Cloud computing platforms offer potential solutions for scalable data analysis.

Purpose of the Study:

  • To evaluate the usability of Microsoft Azure for bioinformatics tasks.
  • To demonstrate the application of Azure for analyzing microarray expression data from ArrayExpress using R.
  • To compare cloud-based analysis on Azure with local computation.

Main Methods:

  • Utilized Microsoft Azure's Platform as a Service (PaaS) for cloud computing.
  • Developed an R script to analyze microarray expression data.
  • Provided a walkthrough guide for Azure-based analysis and compared it to local computation.

Main Results:

  • Azure facilitates the analysis of large microarray expression datasets.
  • The Platform as a Service (PaaS) model on Azure has a steep learning curve for developers accustomed to Linux environments.
  • Azure simplifies the deployment and management of parallel, scalable bioinformatics software with minimal code.

Conclusions:

  • Microsoft Azure is a viable cloud platform for bioinformatics, especially for users needing to run stable software without development involvement.
  • The platform's PaaS offering enables efficient, scalable analysis of large biological datasets.
  • Azure streamlines the deployment of parallel bioinformatics software, making complex analyses more accessible.