Data hazards in synthetic biology

Zelenka, Natalie R., Di Cara, Nina, Sharma, Kieren, Sarvaharman, Seeralan, Ghataora, Jasdeep S., Parmeggiani, Fabio ORCID: https://orcid.org/0000-0001-8548-1090, Nivala, Jeff, Abdallah, Zahraa S., Marucci, Lucia and Gorochowski, Thomas E. 2024. Data hazards in synthetic biology. Synthetic Biology 9 (1) , ysae010. 10.1093/synbio/ysae010

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Abstract

Data science is playing an increasingly important role in the design and analysis of engineered biology. This has been fueled by the development of high-throughput methods like massively parallel reporter assays, data-rich microscopy techniques, computational protein structure prediction and design, and the development of whole-cell models able to generate huge volumes of data. Although the ability to apply data-centric analyses in these contexts is appealing and increasingly simple to do, it comes with potential risks. For example, how might biases in the underlying data affect the validity of a result and what might the environmental impact of large-scale data analyses be? Here, we present a community-developed framework for assessing data hazards to help address these concerns and demonstrate its application to two synthetic biology case studies. We show the diversity of considerations that arise in common types of bioengineering projects and provide some guidelines and mitigating steps. Understanding potential issues and dangers when working with data and proactively addressing them will be essential for ensuring the appropriate use of emerging data-intensive AI methods and help increase the trustworthiness of their applications in synthetic biology.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Pharmacy
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by/4.0/, Type: cc-by
Publisher:	Oxford University Press
Date of First Compliant Deposit:	8 July 2024
Date of Acceptance:	19 June 2024
Last Modified:	09 Oct 2024 13:11
URI:	https://orca.cardiff.ac.uk/id/eprint/170406

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