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.

这项博士学位论文研究改进赠款支持了有关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涉及这种方法。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越来越复杂的任务，超过了个人科学家以进行研究所需的规模生成数据的能力。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成立了名为Biobankss的组织。生物库会产生大量遗传和健康数据，可在许多研究项目中使用。尽管大数据研究无疑是必需的，但它们还将许多关键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。该项目提供了有关生物库设计如何影响人类基因组发现发现的见解。目的是有助于公众对数字技术对人类健康和疾病知识的影响的理解。本研究项目基于认知基础设施的概念来研究跨多个组织的生物群体实践，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；研究社区如何适应其研究的目的是应对这些选择；以及生物库如何随着时间的流逝而变化，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方法，其中包括分析有关生物库设计的技术文献，使用生物库数据生产的研究文献，与生物库进行访谈以及观察他们的工作。在此过程中，这项研究发现了生物库影响基因组研究的机制，并为数据基础设施与科学知识的生产提供了新的观点。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估来通过评估来支持的。