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Efficient similarity search on massive gene data based on cloud computing

机译:基于云计算的海量基因数据高效相似搜索

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As biomedical data grows rapidly nowadays, we are going to study how to efficiently apply cloud computing into biomedical problem. In this paper, the process of solving biomedical problem based on cloud computing is presented. First, the biomedical issue would be focus on the gene match and generation of large amount of the emulated data from real data. Second, a mathematical model is proposed to describe the problem. Third, the mathematical model is implemented into our MapReduce model, which means simulating the biomedical application rested on cloud computing. Finally, some experiments are conducted to test the performance of cloud computing on this issue. Besides, at the end of the paper, some advices are given to doctors and biomedical scientists.
机译:随着当今生物医学数据的快速增长,我们将研究如何有效地将云计算应用于生物医学问题。本文提出了基于云计算的生物医学问题解决过程。首先,生物医学问题将集中在基因匹配和从真实数据中生成大量模拟数据。其次,提出了描述该问题的数学模型。第三,将数学模型实施到我们的MapReduce模型中,这意味着模拟基于云计算的生物医学应用程序。最后,在此问题上进行了一些实验以测试云计算的性能。此外,在本文的最后,还向医生和生物医学科学家提供了一些建议。

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