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A Grid Environment for High-Throughput Proteomics

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9 Author(s)
Cannataro, M. ; Univ. Magna Graecia, Catanzaro ; Barla, A. ; Flor, R. ; Jurman, G.
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We connect in a grid-enabled pipeline an ontology-based environment for proteomics spectra management with a machine learning platform for unbiased predictive analysis. We exploit two existing software platforms (MS-Analyzer and BioDCV), the emerging proteomics standards, and the middleware and computing resources of the EGEE Biomed VO grid infrastructure. In the setup, BioDCV is accessed by the MS-Analyzer workflow as a Web service, thus providing a complete grid environment for proteomics data analysis. Predictive classification studies on MALDI-TOF data based on this environment are presented.

Published in:

NanoBioscience, IEEE Transactions on  (Volume:6 ,  Issue: 2 )

Date of Publication:

June 2007

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