守护者
计算生物学
数据挖掘
集合(抽象数据类型)
DNA
DNA测序
计算机科学
生物
遗传学
政治学
法学
程序设计语言
作者
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 V. Persikov,Helen Scott,Roy Siegelmann,Mona Singh,Allison J. Taggart,Benjamin A. Toll,Kenneth H. Wan,Daniel Wyschogrod,Fusun Yaman,Eric M. Young,S Celniker,Nicholas Roehner
标识
DOI:10.1021/acssynbio.3c00398
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.
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