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DNA-Based Fixed Gain Amplifiers and Linear Classifier Circuits

Zhang, David Yu and Seelig, Georg (2011) DNA-Based Fixed Gain Amplifiers and Linear Classifier Circuits. In: DNA computing and molecular programming. Lecture Notes in Computer Science . No.6518. Springer , Berlin, pp. 176-186. ISBN 978-3-642-18304-1 . https://resolver.caltech.edu/CaltechAUTHORS:20111006-083039035

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Abstract

DNA catalysts have been developed as methods of amplifying single-stranded nucleic acid signals. The maximum turnover (gain) of these systems, however, often varies based on strand and complex purities, and has so far not been well-controlled. Here we introduce methods for controlling the asymptotic turnover of strand displacement-based DNA catalysts and show how these could be used to construct linear classifier systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1007/978-3-642-18305-8_16DOIUNSPECIFIED
http://www.springerlink.com/content/gj36802243123524/PublisherUNSPECIFIED
Additional Information:© 2011 Springer-Verlag Berlin Heidelberg. DYZ is supported by the Fannie and John Hertz Foundation. GS is supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and an NSF CAREER award.
Funders:
Funding AgencyGrant Number
Fannie and John Hertz FoundationUNSPECIFIED
Burroughs Wellcome Fund Career Award at the Scientific Interface UNSPECIFIED
NSF CAREER Award UNSPECIFIED
Series Name:Lecture Notes in Computer Science
Issue or Number:6518
Record Number:CaltechAUTHORS:20111006-083039035
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20111006-083039035
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:27113
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:06 Oct 2011 15:40
Last Modified:03 Oct 2019 03:20

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