High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid

Andreas Quandt (Swiss Institute of Bioinformatics, Switzerland), Sergio Maffioletti (University of Lugano, Switzerland), Cesare Pautasso (Swiss Institute of Bioinformatics, Switzerland), Heinz Stockinger (Swiss Institute of Bioinformatics, Switzerland) and Frederique Lisacek (ETH Zurich, Switzerla)

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DOI: 10.4018/978-1-60566-374-6.ch012

Source title: Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare

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MLA

Quandt, Andreas, Sergio Maffioletti, Cesare Pautasso, Heinz Stockinger and Frederique Lisacek. "High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid." Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare. IGI Global, 2009. 228-244. Web. 22 May. 2013. doi:10.4018/978-1-60566-374-6.ch012

APA

Quandt, A., Maffioletti, S., Pautasso, C., Stockinger, H., & Lisacek, F. (2009). High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid. In M. Cannataro (Ed.), Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare (pp. 228-244). Hershey, PA: Medical Information Science Reference. doi:10.4018/978-1-60566-374-6.ch012

Chicago

Quandt, Andreas, Sergio Maffioletti, Cesare Pautasso, Heinz Stockinger and Frederique Lisacek. "High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid." In Handbook of Research on Computational Grid Technologies for Life Sciences, Biomedicine, and Healthcare, ed. Mario Cannataro, 228-244 (2009), accessed May 22, 2013. doi:10.4018/978-1-60566-374-6.ch012

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Abstract

Proteomics is currently one of the most promising fields in bioinformatics as it provides important insights into the protein function of organisms. Mass spectrometry is one of the techniques to study the proteome, and several software tools exist for this purpose. The authors provide an extendable software platform called swissPIT that combines different existing tools and exploits Grid infrastructures to speed up the data analysis process for the proteomics pipeline.

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Data Provenance in Scientific Workflows (pages 46-59)

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Data Protection and Data Security Regarding Grid Computing in Biomedical Research (pages 76-89)

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Functional Genomics Applications in GRID (pages 149-167)

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High-Throughput GRID Computing for Life Sciences (pages 187-205)

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Management and Analysis of Mass Spectrometry Proteomics Data on the Grid (pages 206-227)

Mario Cannataro (University Magna Graecia of Catanzaro, Italy), Pietro Hiram Guzzi (University Magna Graecia of Catanzaro, Italy), Giuseppe Tradigo (University Magna Graecia of Catanzaro, Italy), Pierangelo Veltri (University Magna Graecia of Catanzaro, Italy)

Recent advances in high throughput technologies analysing biological samples enabled the researchers to collect a huge amount of data. In particular, mass spectromet... Sample PDF | More details...

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12.

High-Throughput Data Analysis of Proteomic Mass Spectra on the SwissBioGrid (pages 228-244)

Proteomics is currently one of the most promising fields in bioinformatics as it provides important insights into the protein function of organisms. Mass spectrometr... Sample PDF | More details...

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13.

Data Mining in Proteomics Using Grid Computing (pages 245-267)

Fotis Psomopoulos (Aristotle University of Thessaloniki, Greece), Pericles Mitkas (Aristotle University of Thessaloniki, Greece)

The scope of this chapter is the presentation of Data Mining techniques for knowledge extraction in proteomics, taking into account both the particular features of m... Sample PDF | More details...

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ProGenGrid: A Grid Problem Solving for Bioinformatics (pages 269-291)

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BioSimGrid Biomolecular Simulation Database (pages 307-326)

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Aspects of Visualization and the Grid in a Biomedical Context (pages 347-362)

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Research environments for modern, cross-disciplinary scientific endeavors have to unite multiple users, with varying levels of expertise and roles, along with multit... Sample PDF | More details...

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Advanced research in life sciences calls for new information technology solutions to support complex, collaborative computer simulations and result analysis. This ch... Sample PDF | More details...

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28.

Leveraging the Power of the Grid with Opal (pages 552-576)

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29.

The LIBI Grid Platform for Bioinformatics (pages 577-613)

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30.

UNICORE: A Middleware for Life Sciences Grid (pages 615-643)

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This chapter provides an overview of Grid middleware and applications related to biomedical and life sciences disciplines. Various technologies, including web-based... Sample PDF | More details...

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31.

A Grid Paradigm for e-Science Applications (pages 644-663)

Livia Torterolo (University of Genoa, Italy), Luca Corradi (University of Genoa, Italy), Barbara Canesi (University of Genoa, Italy), Marco Fato (University of Genoa, Italy), Roberto Barbera (University of Catania and INFN Catania, Italy), Salvatore Scifo (Consorzio Cometa of Catania, Italy), Antonio Calanducci (INFN-)

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32.

gLibrary/DRI: A Grid-Based Platform to Host Muliple Repositories for Digital Content (pages 664-686)

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33.

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34.

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35.

Large-Scale Co-Phylogenetic Analysis on the Grid (pages 731-745)

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Phylogenetic data analysis represents an extremely compute-intensive area of Bioinformatics and thus requires high-performance technologies. Another compute- and mem... Sample PDF | More details...

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Key Terms in this Chapter

Mass Spectrometry: In the field of proteomics, mass spectrometry is a technique to analyze, identify and characterize proteins. In particular, it measures the mass-to-charge ratio.

Grid Workflow: In general, a workflow can be considered as the automation of a specific process which can further be divided into smaller tasks. A Grid workflow consists of several tasks that need to be executed in a Grid environment but not necessarily on the same computing hardware.

High Performance Computing (HPC): HPC is a particular field in computer science that deals with performance optimization of single applications, usually by running parallel instances on high performance computing clusters or supercomputers.

Proteomics: The large-scale study of proteins, their functions and their structures. It is supposed to complement physical genome research. It can also be defined as the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes (http://www.expasy.ch/proteomics_def.html).

High Throughput Computing: In contrast to HPC, high throughput computing does not aim to optimize a single application but several users and applications. In this way, many applications share a computing infrastructure at the same time – in this way the overall throughput of several applications is supposed to be maximized.

Bioinformatics: Comprises the management and the analysis of biological databases.

Grid Job Submission and Execution: Workflows are typically expressed in certain languages and then have to be executed. Often, the entire workflow is called a “job” which needs to be submitted to the Grid and executed on Grid computing resources.

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