Big data bioinformatics

GreeneC.S.; TanJ.; UngM.MooreJ.H.ChengC.

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Big data bioinformatics

机译：大数据生物信息学

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Recent technological advances allow for high throughput profiling of biological systems in a cost-efficient manner. The low cost of data generation is leading us to the "big data" era. The availability of big data provides unprecedented opportunities but also raises new challenges for data mining and analysis. In this review, we introduce key concepts in the analysis of big data, including both "machine learning" algorithms as well as "unsupervised" and "supervised" examples of each. We note packages for the R programming language that are available to perform machine learning analyses. In addition to programming based solutions, we review webservers that allow users with limited or no programming background to perform these analyses on large data compendia.

机译：最近的技术进步允许高分析生物系统的吞吐量有成本效益的方式。一代领先的美国“大数据”时代。大数据提供的可用性前所未有的机遇,也提出了新的挑战数据挖掘和分析。审查,我们引入关键概念的分析的大数据,包括“机器学习”算法以及“无监督”“监督”的例子。可用R编程语言执行机器学习分析。编程基础的解决方案,我们审查网络服务器,允许用户有限或没有执行这些分析编程背景在大数据概略。

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来源
《Journal of Cellular Physiology》 |2014年第12期|1896-1900|共5页
作者
GreeneC.S.; TanJ.; UngM.MooreJ.H.ChengC.;
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作者单位

Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, NH, United States;

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原文格式 PDF
正文语种英语
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关键词
Bioinformatics; data generation; data miningbig dataConceptual Analysispackagesbiological organs;

机译：Bioinformatics;generation;miningbig日期dataConceptual Analysispackagesbiological器官;

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Big data bioinformatics

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