title: Effect of noise in intelligent cellular decision making.
abstract: 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.
authors.affiliation: Department of Mathematics, University College London, London, UK.
authors.forename: Russell
authors.initials: R
authors.lastname: Bates
authors.affiliation: Institute for Women's Health, University College London, London, UK.
authors.forename: Oleg
authors.initials: O
authors.lastname: Blyuss
authors.affiliation: Department of Mathematics, King AbdulAziz University, Jeddah, Saudi Arabia.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Alsaedi
authors.affiliation: Department of Mathematics, University College London, London, UK; Institute for Women's Health, University College London, London, UK; Lobachevsky State University of Nizhniy Novgorod, Nizhniy Novgorod, Russia.
authors.forename: Alexey
authors.initials: A
authors.lastname: Zaikin
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D059629:Signal-To-Noise Ratio