Effect of Noise in Intelligent Cellular Decision Making |
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| Authors: | Russell Bates Oleg Blyuss Ahmed Alsaedi Alexey Zaikin |
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| Affiliation: | 1Department of Mathematics, University College London, London, UK;2Institute for Women’s Health, University College London, London, UK;3Department of Mathematics, King AbdulAziz University, Jeddah, Saudi Arabia;4Lobachevsky State University of Nizhniy Novgorod, Nizhniy Novgorod, Russia;Jiangnan University, CHINA |
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| 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. |
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