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这种方法;也就是说，它们需要来自数千名参与者的数据，以检测基因和健康结果之间的微妙关系。招募参与者和组织他们的数据是一项越来越复杂的任务，超过了单个科学家产生进行研究所需规模数据的能力。为了解决这一差距，各种私人实体，医疗保健提供者，非营利组织，研究集体和政府资助机构已经成立了称为生物库的组织。生物库产生大量的遗传和健康数据，可用于许多研究项目。虽然生物库对于大数据研究无疑是必要的，但它们也将一些关键的数据收集决策从实验室科学家转移到生物库设计师和数据库管理员。该项目提供了关于生物库设计如何影响人类基因组学发现的见解。该研究项目旨在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，考察了多个组织的生物银行实践，这意味着塑造和限制我们如何产生知识的工具。该研究探讨了三个关键问题：生物库如何决定他们将收集哪些数据;研究社区如何调整他们的研究目标以应对这些选择;以及生物库如何随着时间的推移而变化，以应对他们所服务的研究社区内外的压力。为了解决这些问题，该项目采用了混合方法，包括分析有关生物库设计的技术文献，使用生物库数据制作的研究文献，与生物库进行访谈，并观察他们的工作。在此过程中，该研究揭示了生物库影响基因组研究的机制，并为数据基础设施和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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。