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Using metric learning to identify the lab-of-origin of engineered DNA

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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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Fig. 1: Identifying the lab-of-origin of DNA sequences.

References

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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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