Determining the origin of engineered DNA can help to foster responsible innovation within the biotechnology community. A convolutional neural network approach that learns distances between engineered DNA sequences and various labs that could have created them is used to accurately predict the lab-of-origin.
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References
Nielsen, A. A. & Voigt, C. A. Deep learning to predict the lab-of-origin of engineered DNA. Nat. Commun. 9, 3135 (2018). The first study to predict the lab of origin of engineered DNA using deep learning.
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This is a summary of: Soares, I. M. et al. Improving lab-of-origin prediction of genetically engineered plasmids via deep metric learning. Nat. Comput. Sci. https://doi.org/10.1038/s43588-022-00234-z (2022).
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Using metric learning to identify the lab-of-origin of engineered DNA. Nat Comput Sci 2, 296–297 (2022). https://doi.org/10.1038/s43588-022-00240-1
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DOI: https://doi.org/10.1038/s43588-022-00240-1
