A scalable data analysis platform for metagenomics

BigData Conference(2013)

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摘要
With the advent of high-throughput DNA sequencing technology, the analysis and management of the increasing amount of biological sequence data has become a bottleneck for scientific progress. For example, MG-RAST, a metagenome annotation system serving a large scientific community worldwide, has experienced a sustained, exponential growth in data submissions for several years; and this trend is expected to continue. To address the computational challenges posed by this workload, we developed a new data analysis platform, including a data management system (Shock) for biological sequence data and a workflow management system (AWE) supporting scalable, fault-tolerant task and resource management. Shock and AWE can be used to build a scalable and reproducible data analysis infrastructure for upper-level biological data analysis services.
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关键词
metagenomics,workflow,workflow management system,shock,data submissions,genomics,mg-rast,data analysis,scientific progress,upper-level biological data analysis services,biology computing,data analysis platform,biological sequence data,high-throughput dna sequencing technology,awe,cloud computing,dna,bioinformatics,scalable data analysis platform,data management system,metagenome annotation system
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