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A services oriented system for bioinformatics applications on the grid.

Giovanni Aloisio1, Massimo Cafaro, Italo Epicoco

  • 1CACT-NNL/CNR-INFM, CMCC, University of Salento, Lecce, Italy.

Studies in Health Technology and Informatics
|May 4, 2007
PubMed
Summary
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The ProGenGrid system enhances bioinformatics research by enabling the design and execution of in silico experiments through a grid environment. It integrates data sources and bioinformatics tools as web services for efficient biological simulations.

Area of Science:

  • Bioinformatics and computational biology
  • Grid computing and distributed systems
  • Proteomics and genomics

Background:

  • The ProGenGrid system is a distributed grid environment designed as a virtual laboratory for bioinformatics.
  • It supports the creation, execution, and monitoring of in silico experiments.
  • The system leverages web services (WS) for composing data sources and bioinformatics programs, promoting ease of use and reusability.

Purpose of the Study:

  • To describe the evolution and main services of the ProGenGrid system.
  • To highlight its capability in supporting complex bioinformatics workflows.
  • To showcase its application in biological simulations for protein structure prediction and sequence alignment.

Main Methods:

  • Utilizing a Grid-based Problem Solving Environment (PSE).

Related Experiment Videos

  • Wrapping bioinformatics programs and data sources as Web Services (WS).
  • Scheduling composed WS workflows on a grid infrastructure using middleware services.

    • Main Results:

    • ProGenGrid facilitates the composition and execution of bioinformatics workflows.
    • The system supports specific biological simulations, including protein secondary structure prediction and sequence alignment.
    • An enhanced data access service underpins these core functionalities.

    Conclusions:

    • ProGenGrid provides a robust and flexible platform for in silico bioinformatics research.
    • The use of web services and grid middleware enhances the efficiency and accessibility of complex analyses.
    • The system's modular design and focus on key bioinformatics problems demonstrate its value in the field.