Programmability of Chemical Reaction Networks

Programmability of Chemical Reaction Networks

Cached

Download Links

by Matthew Cook , David Soloveichik , Erik Winfree , Jehoshua Bruck

Citations:

7 - 0 self

Versions

Version 0

Version History

Metadata Version 0

Datum	Value	Source
TITLE	Programmability of Chemical Reaction Networks	SVM HeaderParse 0.2
AUTHOR NAME	Matthew Cook	SVM HeaderParse 0.2
AUTHOR AFFIL	1; Institute of Neuroinformatics, UZH, ETH Zürich	SVM HeaderParse 0.2
AUTHOR ADDR	Switzerland	SVM HeaderParse 0.2
AUTHOR NAME	David Soloveichik	SVM HeaderParse 0.2
AUTHOR AFFIL	2; California Institute of Technology, Pasadena	SVM HeaderParse 0.2
AUTHOR ADDR	California, USA	SVM HeaderParse 0.2
AUTHOR NAME	Erik Winfree	SVM HeaderParse 0.2
AUTHOR AFFIL	2; California Institute of Technology, Pasadena	SVM HeaderParse 0.2
AUTHOR ADDR	California, USA	SVM HeaderParse 0.2
AUTHOR NAME	Jehoshua Bruck	SVM HeaderParse 0.2
AUTHOR AFFIL	2; California Institute of Technology, Pasadena	SVM HeaderParse 0.2
AUTHOR ADDR	California, USA	SVM HeaderParse 0.2
ABSTRACT	Summary. Motivated by the intriguing complexity of biochemical circuitry within individual cells we study Stochastic Chemical Reaction Networks (SCRNs), a formal model that considers a set of chemical reactions acting on a finite number of molecules in a well-stirred solution according to standard chemical kinetics equations. SCRNs have been widely used for describing naturally occurring (bio)chemical systems, and with the advent of synthetic biology they become a promising language for the design of artificial biochemical circuits. Our interest here is the computational power of SCRNs and how they relate to more conventional models of computation. We survey known connections and give new connections between SCRNs and	SVM HeaderParse 0.2
CITATIONS	46 found	ParsCit 1.0