Probe Machine

Design and implementation of the dual-center programming platform for ternary optical computer and electronic computer

In order to utilize the advantages of optical computing and promote the application and popularization of Ternary Optical Computer (TOC), this paper proposes a dual-center programming model consisting of electronic processor and optical processor, presents the theory and technologies of the dual-center model in detail, and for the first time explains the SAN ZHI GUANG (SZG) file chain technology, gives the implementation method of the dual-center model. The model tries to effectively manage the resources of optical processor and solve the problem of the distance and network connection mode of using the TOC. Experimental results show that the dual-center model is correct and the implementation method is feasible. It can improve the usability of the TOC and further simplify the TOC programming process, and makes common users apply the TOC and electronic computer to work cooperatively for the same task.

Scalable DNA recognition circuits based on DNA strand displacement

DNA is a kind of nano-molecule considered to be computable on the molecular level, and the precise Watson-Crick principle of base pairing has made it possible for DNA to be a novel computer material. The DNA strand displacement technology has greatly facilitated the development of DNA computing in both logical and intelligent computation. In this paper, we proposed and implemented a molecular recognition circuit based on DNA strand displacement, which can achieve recognition and summation functions. This circuit has a simple molecular composition and is easily scalable. A cross-inhibition module was integrated based upon the molecular recognition circuit to construct a molecular comparator. Considering the advantages of modularity and the experimental feasibility of a scalable recognition circuit, it could be used as a pattern signal recognition and classification module in smart molecular circuits or biosensors.

Exploring the Potential of DNA Computing for Complex Big Data Problems: A Case Study on the Traveling Car Renter Problem

The traveling car renter problem (TCRP) is a variant of the Traveling Salesman Problem (TSP) wherein the salesman utilizes rented cars for travel. The primary objective of this problem is to identify a solution that minimizes the cumulative operating costs. Given its classification as a non-deterministic polynomial (NP) problem, traditional computers are not proficient in effectively resolving it. Conversely, DNA computing exhibits unparalleled advantages when confronted with NP-hard problems. This paper presents a DNA algorithm, based on the Adleman-Lipton model, as a proposed approach to address TCRP. The solution for TCRP can be acquired by following a series of fundamental steps, including coding, interaction, and extraction. The time computing complexity of the proposed DNA algorithm is O(n2m) for TCRP with n cities and m types of cars. By conducting simulation experiments, the solutions for certain instances of TCRP are computed and compared to those obtained by alternative algorithms. The proposed algorithm further illustrates the potential of DNA computing, as a form of parallel computing, to address more intricate large-scale problems.

Key theories and technologies and implementation mechanism of parallel computing for ternary optical computer

Ternary Optical Computer (TOC) is more advanced than traditional computer systems in parallel computing, which is characterized by huge amounts of repeated computations. However, the application of the TOC is still limited because of lack of key theories and technologies. In order to make the TOC applicable and advantageous, this paper systematically elaborates the key theories and technologies of parallel computing for the TOC through a programming platform, including reconfigurability and groupable usability of optical processor bits, parallel carry-free optical adder and the TOC's application characteristics, communication file to express user's needs and data organization method of the TOC. Finally, experiments are carried out to show the effectiveness of the present theories and technologies for parallel computing, as well as the feasibility of the implementation method of the programming platform. For a special instance, it is shown that the clock cycle on the TOC is only 0.26% of on a traditional computer, and the computing resource spent on the TOC is 25% of that on a traditional computer. Based on the study of the TOC in this paper, more complex parallel computing can be realized in the future.

DNA strand displacement based computational systems and their applications

DNA computing has become the focus of computing research due to its excellent parallel processing capability, data storage capacity, and low energy consumption characteristics. DNA computational units can be precisely programmed through the sequence specificity and base pair principle. Then, computational units can be cascaded and integrated to form large DNA computing systems. Among them, DNA strand displacement (DSD) is the simplest but most efficient method for constructing DNA computing systems. The inputs and outputs of DSD are signal strands that can be transferred to the next unit. DSD has been used to construct logic gates, integrated circuits, artificial neural networks, etc. This review introduced the recent development of DSD-based computational systems and their applications. Some DSD-related tools and issues are also discussed.

DNA computing for gastric cancer analysis and functional classification

Early identification of key biomarkers of malignant cancer is vital for patients' prognosis and therapies. There is research demonstrating that microRNAs are important biomarkers for cancer analysis. In this article, we used the DNA strand displacement mechanism (DSD) to construct the DNA computing system for cancer analysis. First, gene chips were obtained through bioinformatical training. These microRNA data and clinical traits were obtained from the Cancer Genome Atlas (TCGA) dataset. Second, we analyzed the expression data by using a weighted gene co-expression network (WGCNA) and found four biomarkers for two clinic features, respectively. Last, we constructed a DSD-based DNA computing system for cancer analysis. The inputs of the system are these identified biomarkers; the outputs are the fluorescent signals that represent their corresponding traits. The experiment and simulation results demonstrated the reliability of the DNA computing system. This DSD simulation system is lab-free but clinically meaningful. We expect this innovative method to be useful for rapid and accurate cancer diagnosis.

Graph Computation Using Algorithmic Self-Assembly of DNA Molecules

DNA molecules have been used as novel computing tools, by which Synthetic DNA was designed to execute computing processes with a programmable sequence. Here, we proposed a parallel computing method using DNA origamis as agents to solve the three-color problem, an example of the graph problem. Each agent was fabricated with a DNA origami of ∼50 nm diameter and contained DNA probes with programmable sticky ends that execute preset computing processes. With the interaction of different nanoagents, DNA molecules self-assemble into spatial nanostructures, which embody the computation results of the three-color problem with polynomial numbers of computing nanoagents in a one-pot annealing step. The computing results were confirmed by atomic force microscopy. Our method is completely different from existing DNA computing methods in its computing algorithm, and it has an advantage in terms of computational complexity and results detection for solving graph problems.

Multiform DNA origami arrays using minimal logic control

Self-assembled DNA nanostructures significantly contribute to DNA nanotechnology. Algorithmic guiding of the assembly of DNA arrays remains a challenge in nanoarchitecture. Usually, the more sophisticated a DNA nanoarchitecture, the more DNA connections with specific sequences are required. This study aimed to investigate the feasibility of using the minimum pairs of DNA connection strands to implement algorithm-based self-assembly with finite DNA origamis. We found that the DNA origami linking complexity was markedly reduced. By rotating and turning the origami tile in different linking directions, we obtained 2 × 2 arrays of DNA origamis using a pair of DNA connections, 2 × 4 arrays using two pairs of DNA connections, and 4 × 4 arrays using three pairs of connection strands. We further analysed the effects of distortion on array formation. Overall, this study presents a hierarchical assembly strategy with minimal connections to generate multi-scale DNA arrays.

Adjusting Linking Strands to Form Size-Controllable DNA Origami Rings

DNA origami is a powerful tool in nanotechnology that can be used to construct arbitrary structures for several nanoengineering applications. Generally, the more complex and sophisticated the construction, the greater is the number of origamis and connection strands that will be needed. Therefore, developing an effective and low-cost method for multiform DNA architecture is important in nanoengineering. Here, we adopted an oblique linking strategy to connect cross-shaped DNA origami with a controlled curing angle. The size of the DNA rings ranged from four blocks of approximately 200 nm to eleven blocks of c.a. 600 nm. We observed that the minimum size of the DNA ring structure was limited by the width of a single block. The largest rings were negatively affected by thermodynamic randomness, and thus, DNA rings consisting of more than eleven blocks were not observed. This strategy facilitates the generation of various DNA origami rings, whose size can be controlled by adjusting the length of the connection strands.

Small Universal Bacteria and Plasmid Computing Systems

Bacterial computing is a known candidate in natural computing, the aim being to construct "bacterial computers" for solving complex problems. In this paper, a new kind of bacterial computing system, named the bacteria and plasmid computing system (BP system), is proposed. We investigate the computational power of BP systems with finite numbers of bacteria and plasmids. Specifically, it is obtained in a constructive way that a BP system with 2 bacteria and 34 plasmids is Turing universal. The results provide a theoretical cornerstone to construct powerful bacterial computers and demonstrate a concept of paradigms using a "reasonable" number of bacteria and plasmids for such devices.

Model Checking Temporal Logic Formulas Using Sticker Automata

As an important complex problem, the temporal logic model checking problem is still far from being fully resolved under the circumstance of DNA computing, especially Computation Tree Logic (CTL), Interval Temporal Logic (ITL), and Projection Temporal Logic (PTL), because there is still a lack of approaches for DNA model checking. To address this challenge, a model checking method is proposed for checking the basic formulas in the above three temporal logic types with DNA molecules. First, one-type single-stranded DNA molecules are employed to encode the Finite State Automaton (FSA) model of the given basic formula so that a sticker automaton is obtained. On the other hand, other single-stranded DNA molecules are employed to encode the given system model so that the input strings of the sticker automaton are obtained. Next, a series of biochemical reactions are conducted between the above two types of single-stranded DNA molecules. It can then be decided whether the system satisfies the formula or not. As a result, we have developed a DNA-based approach for checking all the basic formulas of CTL, ITL, and PTL. The simulated results demonstrate the effectiveness of the new method.

A novel method for multifactorial bio-chemical experiments design based on combinational design theory

Experimental design focuses on describing or explaining the multifactorial interactions that are hypothesized to reflect the variation. The design introduces conditions that may directly affect the variation, where particular conditions are purposely selected for observation. Combinatorial design theory deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. In this work, borrowing the concept of "balance" in combinatorial design theory, a novel method for multifactorial bio-chemical experiments design is proposed, where balanced templates in combinational design are used to select the conditions for observation. Balanced experimental data that covers all the influencing factors of experiments can be obtianed for further processing, such as training set for machine learning models. Finally, a software based on the proposed method is developed for designing experiments with covering influencing factors a certain number of times.

An algorithm based on positive and negative links for community detection in signed networks

Community detection problem in networks has received a great deal of attention during the past decade. Most of community detection algorithms took into account only positive links, but they are not suitable for signed networks. In our work, we propose an algorithm based on random walks for community detection in signed networks. Firstly, the local maximum degree node which has a larger degree compared with its neighbors is identified, and the initial communities are detected based on local maximum degree nodes. Then, we calculate a probability for the node to be attracted into a community by positive links based on random walks, as well as a probability for the node to be away from the community on the basis of negative links. If the former probability is larger than the latter, then it is added into a community; otherwise, the node could not be added into any current communities, and a new initial community may be identified. Finally, we use the community optimization method to merge similar communities. The proposed algorithm makes full use of both positive and negative links to enhance its performance. Experimental results on both synthetic and real-world signed networks demonstrate the effectiveness of the proposed algorithm.