Experimental Demonstration of Hopfield Neural Network using DNA molecules
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Experimental Demonstration of Hopfield Neural Network using DNA molecules Hayri E. Akin1, Dundar Karabay2, Allen P. Mills, Jr2, Cengiz S. Ozkan3 and Mihrimah Ozkan1 1 Department of Electrical Engineering, , 2Department of Physics and Astronomy, 3Department of Mechanical Engineering, University of California Riverside, Riverside, CA 92521, USA ABSTRACT DNA Computing is a rapidly-developing interdisciplinary area which could benefit from more experimental results to solve problems with the current biological tools. In this study, we have integrated microelectronics and molecular biology techniques for showing the feasibility of Hopfield Neural Network using DNA molecules. Adleman‟s seminal paper in 1994 showed that DNA strands using specific molecular reactions can be used to solve the Hamiltonian Path Problem. This accomplishment opened the way for possibilities of massively parallel processing power, remarkable energy efficiency and compact data storage ability with DNA. However, in various studies, small departures from the ideal selectivity of DNA hybridization lead to significant undesired pairings of strands and that leads to difficulties in schemes for implementing large Boolean functions using DNA. Therefore, these error prone reactions in the Boolean architecture of the first DNA computers will benefit from fault tolerance or error correction methods and these methods would be essential for large scale applications. In this study, we demonstrate the operation of six dimensional Hopfield associative memory storing various memories as an archetype fault tolerant neural network implemented using DNA molecular reactions. The response of the network suggests that the protocols could be scaled to a network of significantly larger dimensions. In addition the results are read on a Silicon CMOS platform exploiting the semiconductor processing knowledge for fast and accurate hybridization rates. INTRODUCTION In 1994 Leonard Adleman demonstrated the feasibility of carrying out a computation at the molecular level by using DNA molecules and specific molecular reactions1. In his pioneering paper, he encoded a small graph in DNA molecules and solved an example of the directed Hamiltonian path problem by using the tools of molecular biology. The importance of Adleman‟s study comes from its vision and revealed the possibilities that can be accomplished with DNA in computing. When the ligation or hybridization of two DNA molecules is considered as an operation, approximately 1012 operations can be carried per second with micromoles concentrations. This speed is much bigger than supercomputers. When the energy efficiency of molecular reactions is considered 1 J is enough for 2x1019 operations with DNA compared to 109 operations per J in supercomputers. In the high density information storage area 1 gram of DNA can hold about 1014 MB of data equivalent to 140 trillion CDs1-4. The fundamental reactions in molecular biology, such as Watson-Crick DNA hybridization, ligation and PCR are employed as a part of DNA based computation a
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