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Microbase2.0: A Generic Framework for Computationally Intensive Bioinformatics Workflows in the Cloud

机译:Microbase2.0:云中计算密集型生物信息学工作流程的通用框架

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As bioinformatics datasets grow ever larger, and analyses become increasingly complex, there is a need for data handling infrastructures to keep pace with developing technology. One solution is to apply Grid and Cloud technologies to address the computational requirements of analysing high throughput datasets. We present an approach for writing new, or wrapping existing applications, and a reference implementation of a framework, Microbase2.0, for executing those applications using Grid and Cloud technologies. We used Microbase2.0 to develop an automated Cloud-based bioinformatics workflow executing simultaneously on two different Amazon EC2 data centres and the Newcastle University Condor Grid. Several CPU years' worth of computational work was performed by this system in less than two months. The workflow produced a detailed dataset characterising the cellular localisation of 3,021,490 proteins from 867 taxa, including bacteria, archaea and unicellular eukaryotes. Microbase2.0 is freely available from http://www.microbase.org.uk/.
机译:随着生物信息学数据集增长越来越大,和分析变得越来越复杂,有必要对数据处理的基础设施,以跟上技术发展的步调。一种解决方案是应用网格和云计算技术,以解决高分析通量数据集的计算需求。我们提出了新的写作,或者包装现有的应用程序的方法,以及一个参考实现框架,Microbase2.0,用于执行使用网格和云技术,这些应用程序。我们使用Microbase2.0工作流程在两个不同的Amazon EC2的数据中心,同时执行和纽卡斯尔大学神鹰电网发展自动化基于云计算的生物信息学。被这个系统在不到两个月的时间进行几个CPU多年积累的计算工作。工作流产生的数据集的详细从867类群,包括细菌,古细菌和单细胞真核生物表征3021490种蛋白的细胞定位。 Microbase2.0是免费提供从http://www.microbase.org.uk/。

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