Functional Genomics Computational Assessment of Threats (FunGCAT/IGACAT)

Project Contact: Andrew Warren / Stephen Eubank
Funding Agency: Intelligence Advance Research Projects Activity (IARPA) IARPA

IGACAT is a research project involving a team from five universities led by the University of Virginia that is funded by IARPA’s FunGCAT (Functional Genomics Computational Assessment of Threats) program. Our goal is to assess whether synthesizing specific short strings of DNA would pose a risk. Currently, it is possible to order custom-designed DNA by mail. Synthesis labs are urged to know their customers and to know whether the order is part or all of a “sequence of concern.” We are integrating all the world’s knowledge about genomes with biological expert knowledge through machine learning to build a fast, but accurate, threat classifier for 50-100 base pair nucleotide strings which may be novel or disguised. The methods developed for this project will be useful to a wide range of other applications such as finding and annotating new genes, detecting mutations that lead to anti-microbial resistance, or searching for small-molecule drugs.