National Institute of General Medical Sciences, National Institutes of Health, 9000 Rockville Pike, Bethesda, Marylnd 20892, USA.
Center for Information Technology, National Institutes of Health, 9000 Rockville Pike, Bethesda, Marylnd 20892, USA.
Brief Bioinform. 2024 Jul 23;25(Supplement_1). doi: 10.1093/bib/bbae478.
Biomedical data are growing exponentially in both volume and levels of complexity, due to the rapid advancement of technologies and research methodologies. Analyzing these large datasets, referred to collectively as "big data," has become an integral component of research that guides experimentation-driven discovery and a new engine of discovery itself as it uncovers previously unknown connections through mining of existing data. To fully realize the potential of big data, biomedical researchers need access to high-performance-computing (HPC) resources. However, supporting on-premises infrastructure that keeps up with these consistently expanding research needs presents persistent financial and staffing challenges, even for well-resourced institutions. For other institutions, including primarily undergraduate institutions and minority serving institutions, that educate a large portion of the future workforce in the USA, this challenge presents an insurmountable barrier. Therefore, new approaches are needed to provide broad and equitable access to HPC resources to biomedical researchers and students who will advance biomedical research in the future.
生物医学数据的数量和复杂程度都呈指数级增长，这是由于技术和研究方法的快速进步。分析这些大型数据集，通常称为“大数据”，已成为研究的一个组成部分，指导实验驱动的发现，并通过挖掘现有数据发现以前未知的联系，成为新的发现引擎。为了充分挖掘大数据的潜力，生物医学研究人员需要访问高性能计算 (HPC) 资源。然而，支持能够跟上这些不断扩展的研究需求的本地基础设施，即使对于资源充足的机构来说，也存在持续的财务和人员配置方面的挑战。对于其他机构，包括主要的本科生机构和少数族裔服务机构，它们在美国培养了很大一部分未来的劳动力，这一挑战构成了难以逾越的障碍。因此，需要新的方法来为未来将推动生物医学研究的生物医学研究人员和学生提供广泛和公平的 HPC 资源访问。
