Big data in life sciences and public health

S. Aluru
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Abstract

Summary form only given. The complete presentation was not made available for publication as part of the conference proceedings. The recent proliferation of extremely large datasets due to high-throughput instrumentation in sciences and engineering, ubiquitous deployment of sensors, and birth and rise of social networks, have resulted in numerous data-driven challenges that are now captured by the umbrella term "big data". This talk will have two parts. In the first part, I will brief the audience on the ongoing federal initiatives in Big Data in the United States. The second part will focus on my group's research in big data, focused on supporting applications in the life sciences. In particular, I will describe big data problems arising from advances in high-throughput DNA sequencing and our work on developing parallel methods to support genomic and metagenomic applications driven by these advances.
生命科学和公共卫生领域的大数据
只提供摘要形式。完整的报告没有作为会议记录的一部分提供出版。由于科学和工程领域的高通量仪器、无处不在的传感器部署以及社交网络的诞生和兴起,最近大量数据集的激增导致了许多数据驱动的挑战,这些挑战现在被统称为“大数据”。这次演讲将分为两个部分。在第一部分中,我将向听众简要介绍美国在大数据方面正在进行的联邦举措。第二部分将重点介绍我的小组在大数据方面的研究,重点是在生命科学方面的支持应用。特别是,我将描述高通量DNA测序的进步所带来的大数据问题,以及我们在开发并行方法以支持这些进步驱动的基因组和宏基因组应用方面的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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