Machine learning for synthetic gene circuit engineering.

Sebastian Palacios¹, James J Collins², Domitilla Del Vecchio³

¹Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. Electronic address: spalacio@mit.edu.

²Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215, USA.

³Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

PubMed DOI

Abstract

Synthetic biology leverages engineering principles to program biology with new functions for applications in medicine, energy, food, and the environment. A central aspect of synthetic biology is the creation of synthetic gene circuits - engineered biological circuits capable of performing operations, detecting signals, and regulating cellular functions. Their development involves large design spac…

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