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Cloud Computing for Fluorescence Correlation Spectroscopy Simulations

  • Lucía Marroig
  • Camila Riverón
  • Sergio Nesmachnow
  • Esteban Mocskos
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 565)

Abstract

Fluorescence microscopy techniques and protein labeling set an inflection point in the way cells are studied. The fluorescence correlation spectroscopy is extremely useful for quantitatively measuring the movement of molecules in living cells. This article presents the design and implementation of a system for fluorescence analysis through stochastic simulations using distributed computing techniques over a cloud infrastructure. A highly scalable architecture, accessible to many users, is proposed for studying complex cellular biological processes. A MapReduce algorithm that allows the parallel execution of multiple simulations is developed over a distributed Hadoop cluster using the Microsoft Azure cloud platform. The experimental analysis shows the correctness of the implementation developed and its utility as a tool for scientific computing in the cloud.

Keywords

Scientific computing Cloud Fluorescence analysis 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Lucía Marroig
    • 1
  • Camila Riverón
    • 1
  • Sergio Nesmachnow
    • 1
  • Esteban Mocskos
    • 2
    • 3
  1. 1.Universidad de la RepúblicaMontevideoUruguay
  2. 2.Departamento de Computación, Facultad de Ciencias Exactas y NaturalesUniversidad de Buenos AiresBuenos AiresArgentina
  3. 3.Centro de Simulación Computacional p/Aplic. Tecnológicas/CSC-CONICETBuenos AiresArgentina

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