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云计算中的并行随机系统生物学。

Parallel stochastic systems biology in the cloud.

出版信息

Brief Bioinform. 2014 Sep;15(5):798-813. doi: 10.1093/bib/bbt040. Epub 2013 Jun 18.

Abstract

The stochastic modelling of biological systems, coupled with Monte Carlo simulation of models, is an increasingly popular technique in bioinformatics. The simulation-analysis workflow may result computationally expensive reducing the interactivity required in the model tuning. In this work, we advocate the high-level software design as a vehicle for building efficient and portable parallel simulators for the cloud. In particular, the Calculus of Wrapped Components (CWC) simulator for systems biology, which is designed according to the FastFlow pattern-based approach, is presented and discussed. Thanks to the FastFlow framework, the CWC simulator is designed as a high-level workflow that can simulate CWC models, merge simulation results and statistically analyse them in a single parallel workflow in the cloud. To improve interactivity, successive phases are pipelined in such a way that the workflow begins to output a stream of analysis results immediately after simulation is started. Performance and effectiveness of the CWC simulator are validated on the Amazon Elastic Compute Cloud.

摘要

生物系统的随机建模,结合模型的蒙特卡罗模拟,是生物信息学中越来越流行的技术。模拟分析工作流程可能在计算上非常昂贵,从而降低了模型调整所需的交互性。在这项工作中,我们主张采用高级软件设计作为构建高效、可移植的云并行模拟器的工具。特别是,提出并讨论了基于 FastFlow 模式的系统生物学的 Calculus of Wrapped Components(CWC)模拟器。由于有了 FastFlow 框架,CWC 模拟器被设计成一个高级工作流程,可以在云中的单个并行工作流程中模拟 CWC 模型、合并模拟结果并对其进行统计分析。为了提高交互性,连续的阶段被流水线化,以便在模拟开始后,工作流程立即开始输出分析结果流。在 Amazon Elastic Compute Cloud 上验证了 CWC 模拟器的性能和有效性。

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