Bioprofiling over grid for early detection of dementia

  • Authors:

  • L. Sun;P. Hu;C. Goh;B. Hamadicharef;M. Hess;E. Ifeachor;I. Barbounakis;M. Zervakis;N. Nurminen;A. Varri

  • Affiliations:

  • University of Plymouth, Plymouth, U.K.;University of Plymouth, Plymouth, U.K.;University of Plymouth, Plymouth, U.K.;University of Plymouth, Plymouth, U.K.;University of Plymouth, Plymouth, U.K.;University of Plymouth, Plymouth, U.K.;Technical University of Crete, Kounoupidiana, Chania, Greece and Technological & Educational Institute of Crete, Chania, Greece;Technical University of Crete, Kounoupidiana, Chania, Greece;Tampere University of Technology, Finland;Tampere University of Technology, Finland

  • Venue:
  • InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
  • Year:
  • 2006

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Abstract

The primary aim of this paper is to present a new concept, bioprofiling over Grid, and to illustrate how Grid computing may be used to support individualisation of healthcare in future, with the aid of a new test bed, the BIOPATTERN Grid. The BIOPATTERN Grid is designed to facilitate seamless sharing of geographically distributed bioprofile databases and to support the analysis of bioprofiles to combat major diseases such as brain diseases and cancer within a major EU project, BIOPATTERN (www.biopattern.org). The main objectives in this paper are 1) to report the development of the BIOPATTERN Grid for biopattern analysis and bioprofiling in support of individualisation of healthcare; 2) to illustrate how the BIOPATTERN Grid could be used for biopattern analysis and bioprofiling for early detection of dementia. We present the architecture and general functionalities of BIOPATTERN Grid, and the development of a prototype test bed (including a Grid Portal and Grid services for early detection of dementia). We illustrate the concept of bioprofiling over Grid and discuss issues such as scalability in high through-put computing for biodata analysis associated with bioprofiling for dementia. Results show benefits in both high throughput computing in biodata analysis and for individualisation of healthcare using Grid computing which makes it possible to access geographically distributed patient's information for subject-specific data analysis for early detection of dementia.