DNA-Based Fixed Gain Amplifiers and Linear Classifier Circuits

  • David Yu Zhang
  • Georg Seelig
Conference paper

DOI: 10.1007/978-3-642-18305-8_16

Volume 6518 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Zhang D.Y., Seelig G. (2011) DNA-Based Fixed Gain Amplifiers and Linear Classifier Circuits. In: Sakakibara Y., Mi Y. (eds) DNA Computing and Molecular Programming. DNA 2010. Lecture Notes in Computer Science, vol 6518. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • David Yu Zhang
    • 1
  • Georg Seelig
    • 2
  1. 1.California Institute of TechnologyPasadenaUSA
  2. 2.University of WashingtonSeattleUSA