Towards a Biomolecular Learning Machine

  • Matthew R. Lakin
  • Amanda Minnich
  • Terran Lane
  • Darko Stefanovic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7445)


Learning and generalisation are fundamental behavioural traits of intelligent life. We present a synthetic biochemical circuit which can exhibit non-trivial learning and generalisation behaviours, which is a first step towards demonstrating that these behaviours may be realised at the molecular level. The aim of our system is to learn positive real-valued weights for a real-valued linear function of positive inputs. Mathematically, this can be viewed as solving a non-negative least-squares regression problem. Our design is based on deoxyribozymes, which are catalytic DNA strands. We present simulation results which demonstrate that the system can converge towards a desired set of weights after a number of training instances are provided.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Matthew R. Lakin
    • 1
  • Amanda Minnich
    • 1
  • Terran Lane
    • 1
  • Darko Stefanovic
    • 1
  1. 1.Department of Computer ScienceUniversity of New MexicoAlbuquerqueUSA

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