DNA as a universal substrate for chemical kinetics
By David Soloveichik, Georg Seelig, Erik Winfree. Proceedings of the National Academy of Sciences of the United States of America, 2009
751 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/268eda0ace7825f6a347fffb17f28b8c9b568181
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
In Molecular Biology
- Georg Seelig
- David Y. Zhang
- Sriram Kosuri
- David Soloveichik
- Luca Cardelli
- Andrew Phillips
- George M. Church
- Teruo Fujii
Citations in the corpus
- Large-scale de novo DNA synthesis: technologies and applications (2014, background): “Base-pairing and strand-invasion properties of DNA have also allowed researchers to explore interesting information processing and computational capabilities using small libraries of oligos [129] [130] [131] [132] .”
- Dynamic DNA nanotechnology using strand-displacement reactions. (2011, methodology): “[68] suggested a systematic approach for approximating arbitrary mass action kinetics through DNA strand displacement cascades (Fig.”
- Programmable chemical controllers made from DNA (2013, background): “Among the many proposed architectures for strand displacement computation 2,10–13, 15– 19 ,”
- Reachability bounds for chemical reaction networks and strand displacement systems (2012, background): “CRNs and thus DSDs can in principle simulate Turing-general models of computation (Qian et al. 2011a; Seelig et al. 2006), and DSDs can be energy efficient (Seelig et al. 2006; Soloveichik et al. 2010; Yurke et al. 2000; Zhang and Seelig 2011).”
- Programming an in vitro DNA oscillator using a molecular networking strategy (2011, positive): “This has been used to create spatial static structures at the nanometre scale (Seeman, 2003; Rothemund, 2006), as well as chemical (Yin et al , 2008; Soloveichik et al , 2010) and biochemical (Bath et al , 2005; Win et al , 2009) machines.”