Effect of noise in intelligent cellular decision making

Russell Bates, Oleg Blyuss, Ahmed Alsaedi, Alexey Zaikin

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.

Original languageEnglish
Pages (from-to)e0125079
JournalPLoS ONE
Issue number5
Publication statusPublished - 2015


  • Algorithms
  • Artificial Intelligence
  • Signal-To-Noise Ratio


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