Title :
A Grid Environment for High-Throughput Proteomics
Author :
Cannataro, Mario ; Barla, Annalisa ; Flor, Roberto ; Jurman, Giuseppe ; Merler, Stefano ; Paoli, Silvano ; Tradigo, Giuseppe ; Veltri, Pierangelo ; Furlanello, Cesare
Author_Institution :
Univ. Magna Graecia, Catanzaro
fDate :
6/1/2007 12:00:00 AM
Abstract :
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.
Keywords :
Internet; biology computing; grid computing; learning (artificial intelligence); middleware; molecular biophysics; ontologies (artificial intelligence); proteins; BioDCV; EGEE Biomed VO grid infrastructure; MALDI-TOF data; MS-Analyzer; Web service; grid environment; high-throughput proteomics; machine learning; middleware; ontology; predictive analysis; predictive classification; Biomedical computing; Environmental management; Grid computing; Machine learning; Middleware; Ontologies; Pipelines; Proteomics; Software standards; Web services; Biomarker discovery; feature ranking; grid problem solving environment; machine learning; mass spectrometry; ontology; predictive classification; proteomics; workflow; Artificial Intelligence; Database Management Systems; Databases, Protein; Information Storage and Retrieval; Internet; Mass Spectrometry; Proteome; Proteomics; Sequence Analysis, Protein; Software; Systems Integration; User-Computer Interface;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2007.897495
