Managing bioengineering complexity with AI techniques》.pdf

G Model BIO-3598; No. of Pages 7 ARTICLE IN PRESS BioSystems xxx (2015) xxx–xxx Contents lists available at ScienceDirect BioSystems j o u r n a l h o m e p a g e: w w w. elsev /locate/biosystems Managing bioengineering complexity with AI techniques Jacob Beal ∗ , Aaron Adler, Fusun Yaman Raytheon BBN Technologies, 10 Moulton Street, Cambridge, MA 02138, United States a r t i c l e i n f o a b s t r a c t Article history: Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effec- Received 9 April 2015 tively engineering such systems, however, requires the synthesis of a rapidly expanding and changing Received in revised form 3 August 2015 complex body of knowledge, protocols, and methodologies. Many of the problems in managing this Accepted 14 August 2015 complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, Available online xxx i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational “routine” work and thus better allow humans to focus Keywords: their attention on the deeper scientific and engineering issues. This paper examines the potential impact Synthetic biology of AI on the engin