Implications of Big Data for cell biology.
Implications of Big Data for cell biology.
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DOI：
10.1091/mbc.e13-12-0756
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发表时间：
2015-07-15
影响因子：
3.3
通讯作者：
Troyanskaya OG
中科院分区：
文献类型：
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作者：
Dolinski K;Troyanskaya OG
《大数据》已经超越《系统生物学》和《组学》成为生物科学领域最热门的热词，但炒作背后有什么实质内容吗？当然，我们已经从过去15-20年来公布的许多单独的高通量数据集中了解到了细胞和分子生物学的各个方面。这些数据虽然作为单独的数据集很有用，但在使用大数据方法进行询问时，可以提供更多的知识，例如应用综合方法来利用整个异类数据概要。在这里，我们讨论这种大数据方法在生物学中的好处和挑战，以及细胞和分子生物学家如何最好地利用它们。
“Big Data” has surpassed “systems biology” and “omics” as the hottest buzzword in the biological sciences, but is there any substance behind the hype? Certainly, we have learned about various aspects of cell and molecular biology from the many individual high-throughput data sets that have been published in the past 15–20 years. These data, although useful as individual data sets, can provide much more knowledge when interrogated with Big Data approaches, such as applying integrative methods that leverage the heterogeneous data compendia in their entirety. Here we discuss the benefits and challenges of such Big Data approaches in biology and how cell and molecular biologists can best take advantage of them.