Data integration in the era of omics: current and future challenges.
Data integration in the era of omics: current and future challenges.
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DOI：
10.1186/1752-0509-8-s2-i1
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发表时间：
2014
影响因子：
--
通讯作者：
Tegnér J
中科院分区：
文献类型：
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作者：
Gomez-Cabrero D;Abugessaisa I;Maier D;Teschendorff A;Merkenschlager M;Gisel A;Ballestar E;Bongcam-Rudloff E;Conesa A;Tegnér J
如何整合异构的大型组学数据不仅是一个概念上的挑战，也是日常组学数据分析中的一个实际障碍。随着新的组学技术的兴起和通过大规模的财团项目，生物系统正在以前所未有的规模进行进一步研究，产生异质的，往往是大数据集。这些数据集鼓励研究人员开发新的数据集成方法。在这个介绍中，我们回顾的定义和特点，目前的努力，在生命科学中的数据集成。我们已经使用了网络调查，以评估目前的研究项目的数据整合，以挖掘到的观点，需求和挑战，目前所认为的部分研究界。
To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community.