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Parallel stochastic systems biology in the cloud.

Marco Aldinucci, Massimo Torquati, Concetto Spampinato

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    |June 20, 2013
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    Summary
    This summary is machine-generated.

    This study presents a cloud-based parallel simulator for biological systems modeling. It enhances interactivity by pipelining simulation and analysis, making complex bioinformatics workflows more efficient.

    Keywords:
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    Area of Science:

    • Bioinformatics
    • Computational Biology
    • Systems Biology

    Background:

    • Stochastic modeling and Monte Carlo simulations are vital in bioinformatics but can be computationally expensive.
    • Current simulation-analysis workflows often lack the interactivity needed for efficient model tuning.

    Purpose of the Study:

    • To advocate for high-level software design in creating efficient, portable, parallel cloud simulators.
    • To introduce the Calculus of Wrapped Components (CWC) simulator, built using the FastFlow pattern-based approach.

    Main Methods:

    • Designed the CWC simulator using the FastFlow framework for a high-level, pipelined workflow.
    • Integrated simulation, result merging, and statistical analysis into a single parallel cloud workflow.
    • Pipelined successive workflow phases to enable immediate analysis results.

    Main Results:

    • The CWC simulator efficiently handles simulation, merging, and analysis of biological models in the cloud.
    • Pipelining significantly improved interactivity by providing early access to analysis results.
    • The simulator's performance and effectiveness were validated on Amazon Elastic Compute Cloud.

    Conclusions:

    • High-level software design, exemplified by the CWC simulator and FastFlow, enables efficient parallel cloud simulations.
    • Pipelined workflows enhance user interactivity in complex computational biology tasks.
    • The CWC simulator offers a validated solution for computationally intensive bioinformatics analyses on cloud platforms.