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GAAIN Virtual Appliances: Virtual Machine Technology for Scientific Data Analysis

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Data Integration in the Life Sciences (DILS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9162))

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Abstract

We present our experience with technology for developing virtual machines and virtual appliances. Our goal is to facilitate scientific workflow sharing and analysis for scientific investigation using virtual machine technology. Our work is in the context of a larger effort on building an efficient data sharing and analysis network for data providers as well as scientific investigators in the domain of Alzheimer’s Disease (AD) research.

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Notes

  1. 1.

    www.gaain.org.

  2. 2.

    www.loni.usc.edu/Software/Pipeline.

  3. 3.

    www.aws.amazon.com/ec2/.

  4. 4.

    www.vmware.com.

  5. 5.

    www.aws.amazon.com.

  6. 6.

    www.azure.microsoft.com.

  7. 7.

    www.susestudio.com.

  8. 8.

    www.oracle.com.

  9. 9.

    www.citrix.com.

  10. 10.

    www.vbridge.com.

  11. 11.

    www.proxmox.com.

  12. 12.

    www.parallels.com.

  13. 13.

    www.ibm.com.

  14. 14.

    www.docker.com.

  15. 15.

    www.parallels.com.

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Author information

Authors and Affiliations

  1. Laboratory of Neuroimaging, Keck School of Medicine of USC, Institute for Neuroimaging and Informatics, University of Southern California, 2001 N Soto Street, Los Angeles, USA

    Arihant Patawari

Authors
  1. Arihant Patawari
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Correspondence to Arihant Patawari .

Editor information

Editors and Affiliations

  1. USC Stevens Neuroimaging and Informatics Institute, Los Angeles, California, USA

    Naveen Ashish

  2. USC Information Sciences Institute, Marina del Rey, California, USA

    Jose-Luis Ambite

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© 2015 Springer International Publishing Switzerland

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Patawari, A. (2015). GAAIN Virtual Appliances: Virtual Machine Technology for Scientific Data Analysis. In: Ashish, N., Ambite, JL. (eds) Data Integration in the Life Sciences. DILS 2015. Lecture Notes in Computer Science(), vol 9162. Springer, Cham. https://doi.org/10.1007/978-3-319-21843-4_21

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  • DOI: https://doi.org/10.1007/978-3-319-21843-4_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21842-7

  • Online ISBN: 978-3-319-21843-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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