Using PROTEUS for modeling Data Mining analysis of proteomics experiments on the Grid

Mario Cannataro, Pietro Hiram Guzzi, Tommaso Mazza, Pierangelo Veltri

Research output: Contribution to journalArticle

Abstract

Novel experiments in bio-medical domain involve different technologies such as mass spectrometry, bio-molecular profiling, nanotechnology, drug design, and of course bioinformatics. Bioinformatics platforms should support both modelling of experiments, and collection, storing and analysis of the produced data. The advent of proteomics has brought with it the hope of discovering novel biomarkers that can be used for early detection, prognosis and treatment of diseases. Mass Spectrometry (MS) is widely used for the mass spectral identification of the thousands of proteins that populate complex biosystems such as serum and tissue. Data Mining (DM) is the semi-automated extraction of patterns representing knowledge implicitly stored in large databases. The combined use of MS with DM is a novel approach in proteomic pattern analysis and is emerging as an effective method for the early diagnosis of diseases. However, it involves large data storage and computing power so it is natural to consider Grid as a reference environment. The paper presents how PROTEUS, a Grid-based Problem Solving Environment for bioinformatics applications, allows formulating, modelling and designing of proteomics experiments involving DM analysis of MS data.

Original languageEnglish
Pages (from-to)232-243
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3292
Publication statusPublished - 2004

Fingerprint

Data Mining
Proteomics
Mass Spectrometry
Mass spectrometry
Data mining
Bioinformatics
Computational Biology
Grid
Modeling
Experiment
Hope
Experiments
Problem Solving Environment
Drug Design
Nanotechnology
Pattern Analysis
Information Storage and Retrieval
Prognosis
Large Data
Biomarkers

Keywords

  • Biomarker discovery
  • Data Mining
  • Grid-based Problem Solving Environment
  • Mass Spectrometry
  • Ontology
  • Workflow

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

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