Microbe-IQ Reads Genomes for Signs of Engineering

Field notes

Microbe-IQ describes a two-part analysis pipeline: detect mobile genetic elements such as plasmids, insertion sequences, and prophages, then assess whether an acquisition appears natural or engineered from evidence at the insertion site. The site attributes its lineage-aware genomic machine-learning foundation to work developed at Georgia Tech and says it was validated on thousands of Pseudomonas aeruginosa genomes. The project identifies itself as a pre-incorporation venture led by Dr. Elijah Mehlferber in partnership with the Brown Lab.