Stochastic resonance in an intracellular genetic perceptron

Russell Bates, Oleg Blyuss, Alexey Zaikin

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)
29 Downloads (Pure)

Abstract

Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity.

Original languageEnglish
Pages (from-to)032716
JournalPhysical Review E
Volume89
Issue number3
DOIs
Publication statusPublished - Mar 2014

Keywords

  • Animals
  • Artificial Intelligence
  • Gene Expression Regulation/genetics
  • Gene Regulatory Networks/genetics
  • Humans
  • Models, Genetic
  • Models, Statistical
  • Neural Networks, Computer
  • Proteome/genetics
  • Stochastic Processes
  • Transcription, Genetic/genetics

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