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尼格姆斯沙盒:一个学习平台,以实现生物医学研究的云计算民主化.

Ming Lei1, Lakshmi K Matukumalli1, Krishan Arora1

  • 1National Institute of General Medical Sciences, National Institutes of Health, 9000 Rockville Pike, Bethesda, Marylnd 20892, USA.

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概括

生物医学研究产生了大量的数据集,需要高性能计算 (HPC). 公平地获得HPC资源对于未来的科学发现和培训下一代研究人员至关重要.

关键词:
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科学领域:

  • 生物医学信息学 生物医学信息学
  • 计算生物学 计算生物学
  • 大数据分析大数据分析

背景情况:

  • 生物医学数据的数量和复杂性正在迅速增加.
  • 分析大数据驱动研究发现,并揭示新的连接.
  • 高性能计算 (HPC) 对于处理大型生物医学数据集至关重要.

研究的目的:

  • 突出在生物医学研究中对高性能计算 (HPC) 的日益增长的需求.
  • 确定机构在提供本地HPC基础设施时所面临的挑战.
  • 倡导新的方法,以公平地获得HPC资源.

主要方法:

  • 该研究分析了生物医学大数据生成的当前环境.
  • 它考察了研究机构面临的基础设施和资源挑战.
  • 它讨论了对培训未来生物医学研究人员的影响.

主要成果:

  • 内部高压计算基础设施面临着重大的财务和人事挑战.
  • 这些挑战对于主要是本科和为少数民族服务的机构来说尤其严重.
  • 现有的障碍限制了许多研究人员和学生获得基本计算资源的机会.

结论:

  • 公平获得HPC对于推动生物医学研究至关重要.
  • 需要新的战略来克服基础设施障碍.
  • 确保对HPC的广泛访问将赋予未来的生物医学劳动力.