Doctoral Dissertation Research Improvement Grant: Biobanking, Epistemic Infrastructure, and the Lifecycle of Genomic Data

博士论文研究改进补助金：生物样本库、认知基础设施和基因组数据的生命周期

• 批准号: 2341622
• 负责人: Kelly Gates
• 金额: $ 2.31万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2341622&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Improvement; Grant

This doctoral dissertation research improvement grant supports a project on the use of big data science methods in genomics. Much of the research in genomics involves the use such methods; that is to say, they require data from thousands of participants in order to detect subtle relationships between genes and health outcomes. The work of recruiting participants and organizing their data is an increasingly complex task, outpacing the ability of individual scientists to produce data at the scale they need to conduct research. To address this gap, a variety of private entities, healthcare providers, nonprofits, research collectives and governmental funding agencies have formed organizations called biobanks. Biobanks produce large amounts of genetic and health data that can be used across a number of research projects. While biobanks are undoubtedly necessary for big data research, they also transfer a number of critical data collection decisions from laboratory scientists to biobank designers and database administrators. This project offers insights into how biobank design affects discovery in human genomics. The aim is to contribute to public understanding of the impact of digital technologies on knowledge of human health and disease.This research project examines biobanking practices across multiple organizations, building on the concept of epistemic infrastructures, meaning the tools that shape and constrain how we produce knowledge. The research explores three key questions: How biobanks make decisions about which data they will collect; how research communities adapt their research aims in response to those choices; and how biobanks change over time in response to pressures from both within and outside of the research communities they serve. To address these questions, the project uses a mixed-methods approach, which includes analyzing technical literature about biobank design, research literature produced using biobank data, conducting interviews with biobankers, and observing their work. In the process, this research uncovers the mechanisms by which biobanks influence genomic research and offers a new perspective on the relationship between data infrastructures and the production of scientific knowledge.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该博士论文研究改进补助金支持在基因组学中使用大数据科学方法的项目。基因组学的许多研究都涉及使用此类方法。也就是说，他们需要数千名参与者的数据才能检测基因与健康结果之间的微妙关系。招募参与者和组织数据的工作是一项日益复杂的任务，超出了科学家个体生成研究所需规模数据的能力。为了弥补这一差距，各种私人实体、医疗保健提供者、非营利组织、研究团体和政府资助机构成立了称为生物银行的组织。生物样本库产生大量遗传和健康数据，可用于许多研究项目。虽然生物样本库无疑对于大数据研究是必要的，但它们也将许多关键数据收集决策从实验室科学家转移到生物样本库设计者和数据库管理员。该项目提供了有关生物样本库设计如何影响人类基因组学发现的见解。目的是帮助公众了解数字技术对人类健康和疾病知识的影响。该研究项目以认知基础设施的概念为基础，研究多个组织的生物样本库实践，即塑造和限制我们生产方式的工具知识。该研究探讨了三个关键问题：生物样本库如何决定收集哪些数据；研究团体如何根据这些选择调整其研究目标；以及生物样本库如何随着时间的推移而变化，以应对其所服务的研究界内外的压力。为了解决这些问题，该项目采用了混合方法，包括分析有关生物样本库设计的技术文献、使用生物样本库数据产生的研究文献、对生物样本库人员进行访谈以及观察他们的工作。在此过程中，这项研究揭示了生物样本库影响基因组研究的机制，并为数据基础设施与科学知识生产之间的关系提供了新的视角。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准。