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IEEE Transactions on Biomedical Circuits and Systems (19324545)18(3)pp. 478-497
In the last few decades, DNA-based self-assembly tiles has become a hot field in research due to its special applications and advantages. The regularity and strong design methods comprise other DNA-based digital circuit design methods. In addition to the obvious advantages of this method, there are challenges in performing computations based on self-assembly tiles, which have hindered the development and construction of large computing circuits with this method. The first challenge is the creation of crystals from DNA molecules in the output, which has led to the impossibility of cascading. The second challenge of this method is the uncontrollability of the reactions of the tiles, which increases the percentage of computing errors. In this article, these two challenges have been solved by changing the structure of leading tiles so that without the activator strand, tiles remain inactive and cannot be connected to other tiles. Also, when the tiles are activated, single-strand DNA will be released after connecting to other tiles, which will be used as the output of the circuit. This output gives the possibility of cascading to self-assembly designed circuits. The method introduced in this article can be a beginning for the re-development of DNA-based circuit design with the self-assembly tile method. © 2007-2012 IEEE.
Journal of Supercomputing (15730484)79(2)pp. 1426-1450
The need for computation speed is ever increasing. A promising solution for this requirement is parallel computing but the degree of parallelism in electronic computers is limited due to the physical and technological barriers. DNA computing proposes a fascinating level of parallelism that can be utilized to overcome this problem. This paper presents a new computational model and the corresponding design methodology using the massive parallelism of DNA computing. We proposed an automatic design algorithm to synthesis the logic functions on the DNA strands with the maximum degree of parallelism. In the proposed model, billions of DNA strands are utilized to compute the elements of the Boolean function concurrently to reach an extraordinary level of parallelism. Experimental and analytic results prove the feasibility and efficiency of the proposed method. Moreover, analyses and results show that a delay of a circuit in this method is independent of the complexity of the function and each Boolean function can be computed with O(1) time complexity. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Scientia Iranica (23453605)30(4 D)pp. 1279-1295
DNA computing is a new kind of computation for solving complex problems with signi cant parallelism. Research ndings indicate that DNA-based logic systems can be useful in many biomedical applications such as early cancer detection. DNA logic systems have been applied successfully to detect the risky patterns of nucleotide-based cancer biomarkers (microRNAs). Detection of real diseases requires large-scale DNA-based logical systems. Therefore, the issue of large-scale DNA-based logic circuits is a crucial research topic. In this paper, an automatic design ow is proposed to facilitate the design, veri cation, and physical implementation of multi-stage and large-scale DNA logic circuits. Digital Micro uidic Biochips (DMFB) have been used recently as a promising platform for efficient implementation of DNA-based computing systems and circuits. We used this technology as the physical platform for implementation of DNA-based circuits. Our experiments and implementations show the feasibility, accuracy, efficiency, and simplicity of the proposed design ow. Final DNA reactions that are synthesized by the proposed design ow are veri ed and simulated using stochastic DNA-reaction simulators to prove the correctness of the proposed design ow. This design ow can open a new horizon for researchers and scientists to design, implement, and evaluate the DNA-based logic systems. © 2023 Sharif University of Technology. All rights reserved.
Microprocessors and Microsystems (01419331)61pp. 217-226
DNA is known as the building block of live organisms for storing the life codes and transferring the genetic features through the generations. However, it is found that DNA strands can be used for a new kind of computation. DNA computation proposes a new level of impressive degree of parallelism that is not feasible with conventional electronic computers. However, available computational models cannot be used for massive parallelism in DNA computing and new computation models and techniques should be developed. In this paper, a new computational model and methodology is proposed to use the massive parallelism of DNA-based circuits. In the proposed model, billions of DNA strands are utilized to compute the elements of the Boolean function concurrently to reach a high level of parallelism. Simulation and analytical results prove the feasibility and efficiency of the proposed method. Moreover, analyses and results show that delay of a circuit in this method is independent from the complexity of the function and each Boolean function can be computed with O(1) time complexity. © 2018
IEEE Transactions on Biomedical Circuits and Systems (19324545)11(5)pp. 1077-1086
DNA is known as the building block for storing the life codes and transferring the genetic features through the generations. However, it is found that DNA strands can be used for a new type of computation that opens fascinating horizons in computational medicine. Significant contributions are addressed on design of DNA-based logic gates for medical and computational applications but there are serious challenges for designing the medium and large-scale DNA circuits. In this paper, a new microarchitecture and corresponding design flow is proposed to facilitate the design of multistage large-scale DNA logic systems. Feasibility and efficiency of the proposed microarchitecture are evaluated by implementing a full adder and, then, its cascadability is determined by implementing a multistage 8-bit adder. Simulation results show the highlight features of the proposed design style and microarchitecture in terms of the scalability, implementation cost, and signal integrity of the DNA-based logic system compared to the traditional approaches. © 2007-2012 IEEE.
DNA is known as the basic element for storing the life codes and transferring the genetic features through the generations. However, it is found that DNA molecules can be utilized for a new kind of computation that opens fascinating horizons in computation and medical sciences. Significant contributions are addressed on design of DNA-based logic gates for medical and computational applications. Microfluidic biochips are known as efficient platforms to implement the DNA circuits but current biochips architectures allow sequential implementation of DNA modules that leads to increase the run time. In this paper, a new Microfluidic biochip architecture and corresponding CAD flow is presented for parallel implementation of DNA circuits. In this flow, Verilog description of the circuit files are synthesized and converted into a bioassay file format. Then assay files are implemented on a microfluidic biochip based on parallel architecture that mane is PBCM architecture. Experimental results show that the experimental time of assays and pin number of biochips are reduced by 17% and 23% respectively. © 2017 IEEE.
Beiki, Z.,
Mirzakuchaki, S.,
Soryani, M.,
Mozayani, N. Journal of Computational and Theoretical Nanoscience (15461955)9(5)pp. 627-630
Majority and inverter gates together make a universal set of Boolean primitives in Quantum-dot Cellular Automata (QCA) circuits. However, an experimental evaluation has shown that MV is not efficiently used during technology mapping by existing logic-synthesis tools. In this paper, we propose an approach, based on Genetic Algorithm, which reduces the area size of QCA circuits. Simulation results show that the proposed method is able to reduce area in QCA circuits design. Copyright © 2012 American Scientific Publishers All rights reserved.
Quantum cellular automata (QCA) is a new nanotechnology that has attracted attentions due to its lower power consumption, smaller size and higher speed compared to CMOS technology. Majority and inverter gates together make a universal set in QCA circuits. An important step in designing QCA circuits is reducing the number of required cells. This paper introduces the structure of QCA and its basic circuits and then proposes a method to reduce the number of cells used in designing these circuits based on genetic algorithm. The results of this method compared with previous methods indicate a significant improvement in terms of number of cells used in the synthesis of QCA circuits. © 2011 IEEE.
