A more effective experimental design for engineering a cell

A new machine-learning approach helps scientists more efficiently identify the optimal intervention to achieve a certain outcome in a complex system, such as genome regulation, requiring far fewer experimental trials than other methods.

Related Keywords

Themistoklisp Sapsis , Caroline Uhler , Jiaqi Zhang , Harvard University , Watson Ai Lab , Broad Institute , Department Of Electrical Engineering , Office Of Naval Research , Wendy Schmidt Center , Institute For Data , Office Of Scientific Research , National Science Foundation Graduate Fellowship , Laboratory For Information , Electrical Engineering , Computer Science , Decision Systems , Nature Machine Intelligence , Wendy Schmidt Center Fellow , Naval Research , Machine Learning , Simons Investigator Award , Air Force Office , Scientific Research , National Science Foundation Graduate ,