Ensemble Detection of DNA Engineering Signatures

Aaron Adler,Joel S. Bader, Brian Basnight,Benjamin W. Booth, Jitong Cai, Elizabeth Cho,Joseph H. Collins,Yuchen Ge, John Grothendieck,Kevin Keating, Tyler Marshall,Anton Persikov, Helen Scott, Roy Siegelmann,Mona Singh, Allison Taggart, Benjamin Toll,Kenneth H. Wan, Daniel Wyschogrod, Fusun Yaman,Eric M. Young,Susan E. Celniker, Nicholas Roehner

ACS SYNTHETIC BIOLOGY(2024)

引用 0|浏览1
暂无评分
摘要
Synthetic biology is creating genetically engineered organisms at an increasing rate for many potentially valuable applications, but this potential comes with the risk of misuse or accidental release. To begin to address this issue, we have developed a system called GUARDIAN that can automatically detect signatures of engineering in DNA sequencing data, and we have conducted a blinded test of this system using a curated Test and Evaluation (T&E) data set. GUARDIAN uses an ensemble approach based on the guiding principle that no single approach is likely to be able to detect engineering with perfect accuracy. Critically, ensembling enables GUARDIAN to detect sequence inserts in 13 target organisms with a high degree of specificity that requires no subject matter expert (SME) review.
更多
查看译文
关键词
artificial intelligence,bioinformatics,biosecurity,engineering detection,machinelearning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要