A Grid-Enabled Gateway for Biomedical Data Analysis

  • Authors:

  • Shayan Shahand;Mark Santcroos;Antoine H. Kampen;Sílvia Delgado Olabarriaga

  • Affiliations:

  • Bioinformatics Laboratory, Department of Clinical Epidemiology Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands;Bioinformatics Laboratory, Department of Clinical Epidemiology Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands;Bioinformatics Laboratory, Department of Clinical Epidemiology Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands and Biosystems Data An ...;Bioinformatics Laboratory, Department of Clinical Epidemiology Biostatistics and Bioinformatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands

  • Venue:
  • Journal of Grid Computing
  • Year:
  • 2012

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Abstract

Biomedical researchers can leverage Grid computing technology to address their increasing demands for data- and compute-intensive data analysis. However, usage of existing Grid infrastructures remains difficult for them. The e-infrastructure for biomedical science (e-BioInfra) is a platform with services that shield middleware complexities, in particular workflow management and monitoring. These services can be invoked from a web-based interface, called e-BioInfra Gateway, to perform large scale data analysis experiments, such that the biomedical researchers can focus on their own research problems. The gateway was designed to simplify usage both by biomedical researchers and e-BioInfra administrators, and to support straightforward extensions with new data analysis methods. In this paper we present the architecture and implementation of the gateway, also showing statistics for its usage. We also share lessons learned during the gateway development and operation. The gateway is currently used in several biomedical research projects and in teaching medical students the principles of data analysis.