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Towards Composing Data Aware Systems Biology Workflows on Cloud Platforms: A MeDICi-Based Approach

机译:致力于在云平台上组成数据感知系统生物学工作流程:一种基于MeDICi的方法

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Cloud computing is being increasingly adopted for deploying systems biology scientific workflows. Scientists developing these workflows use a wide variety of fragmented and competing data sets and computational tools of all scales to support their research. To this end, the synergy of client side workflow tools with cloud platforms is a promising approach to share and reuse data and workflows. In such systems, the location of data and computation is essential consideration in terms of quality of service for composing a scientific workflow across remote cloud platforms. In this paper, we describe a cloud-based workflow for genome annotation processing that is underpinned by MeDICi -- a middleware designed for data intensive scientific applications. The workflow implementation incorporates an execution layer for exploiting data locality that routes the workflow requests to the processing steps that are colocated with the data. We demonstrate our approach by composing two workflows with the MeDICi pipelines.
机译:云计算越来越多地用于部署系统生物学科学工作流程。开发这些工作流的科学家使用各种分散且相互竞争的数据集以及各种规模的计算工具来支持他们的研究。为此,客户端工作流工具与云平台的协同作用是一种有前途的共享和重用数据和工作流的方法。在这样的系统中,数据和计算的位置是在跨远程云平台组成科学工作流的服务质量方面必不可少的考虑因素。在本文中,我们描述了一种基于基因组注释处理的基于云的工作流程,该工作流程由MeDICi支撑-MeDICi是一种为数据密集型科学应用设计的中间件。工作流实现包含一个执行层,用于利用数据局部性,该数据局部性将工作流请求路由到与数据共存的处理步骤。我们通过将两个工作流程与MeDICi管道进行组合来演示我们的方法。

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