dc.date.accessioned | 2023-12-18T21:11:48Z | |
dc.date.available | 2023-12-18T21:11:48Z | |
dc.date.issued | 2023-12-18 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/153197 | |
dc.description.abstract | A Laboratory team is using machine learning to trace the origin of DNA modifications. While previous studies focused on using plasmids—extra-chromosomal pieces of DNA—this team focused on trying to pinpoint exact computational tools used for editing the genome. The results of their work show that it may be possible to trace the origin of modifications back to a specific program, which may help identify the culprit in any attack involving genetic modification. | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | The Bulletin; | |
dc.rights | Attribution-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nd/3.0/us/ | * |
dc.subject | Machine Learning | en_US |
dc.title | Using Machine Learning to Trace Genetically Engineered DNA | en_US |
dc.type | Article | en_US |