20.500.12556/RUL-155774 Synthetic biological neural networks from current implementations to future perspectives Artificial neural networks, inspired by the biological networks of the human brain, have become game-changing computing models in modern computer science. Inspired by their wide scope of applications, synthetic biology strives to create their biological counterparts, which we denote synthetic biological neural networks (SYNBIONNs). Their use in the fields of medicine, biosensors, biotechnology, and many more shows great potential and presents exciting possibilities. So far, many different synthetic biological networks have been successfully constructed, however, SYNBIONN implementations have been sparse. The latter are mostly based on neural networks pretrained in silico and being heavily dependent on extensive human input. In this paper, we review current implementations and models of SYNBIONNs. We briefly present the biological platforms that show potential for designing and constructing perceptrons and/or multilayer SYNBIONNs. We explore their future possibilities along with the challenges that must be overcome to successfully implement a scalable in vivo biological neural network capable of online learning. neural networks perceptron synthetic biology molecular computing neuromorphic computing modelling and simulation nevronske mreže sintezna biologija molekularno računalništvo nevromorfno računalništvo modeliranje in simulacije true false true Angleški jezik Slovenski jezik Članek v reviji 2024-04-17 12:52:09 2024-04-17 12:52:10 2024-05-22 15:10:06 0000-00-00 00:00:00 2024 0 0 11 str. art. 105164 Vol. 237 Mar. 2024 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:575.112 0303-2647 10.1016/j.biosystems.2024.105164 187310083 1-s2.0-S0303264724000492-main.pdf 1-s2.0-S0303264724000492-main.pdf 1 82B2F117448D70253351D52A0F4843AC cb4520806620754191e38f1fe4ed884d03e14a661b6575f34b80765bc98dda3d 15cd07b8-fca9-11ee-85a5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=182861 https://www.sciencedirect.com/science/article/pii/S0303264724000492 0 899ba8a5-fca8-11ee-85a5-0050569b8976 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=182858 Fakulteta za računalništvo in informatiko 0 0 0