DNA computer revolutions

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BEIJING: (Web Desk) In the world of computing, the “DNA computer revolutions ” are in a dimension.

Revoluyions of DNA computer

In which molecular biology, biochemistry and DNA are used to build hardware and DNA itself circuits. It perform computations by summation.

A practical experiment by Fei Wang and colleagues at Shanghai Jiaotong University in China showed that a liquid computer could run more than 100 billion different simple programs using strands of DNA.

Just as when you enter a command on a traditional digital computer, it directs the electrons through specific paths.

These paths on the silicon chip, these circuit configurations each corresponding to different mathematical operations.

But in a computer built with the help of biochemistry and molecular biology.

DNA molecules act as wires and instruct the wires to be arranged in specific ways, creating versatile biological computer circuits.

To replace these circuits and wiring with DNA, Wang and his team at Jiaotong University combined small segments of DNA into larger structures that can be used to create circuit components, such as wires, or those wires in different configurations. can work.

Wang and his team filled tubes with DNA strands and a buffer fluid and linked them together into larger molecules.

The researchers also equipped all the molecules with fluorescence markers.

In this experiment, Wang and his team combined three DPGAs of 500 DNA strands to create a circuit that solves quadratic equations, as well as a circuit for quadratic equations.

In these circuits they incorporated molecules of a specific shape

and a number that participated in a chemical reaction with these molecules, resulting in a circuit similar to moving electrons.

Directions for Future Development and Potential Approaches

Scaling-Up

The executable program complexity of a computing system is closely tied to the number of computing elements it incorporates. Much like the evolution of other computational machines, enhancing circuit scale stands out as a pivotal direction for advancement. In the early stages, the first modern electronic computer, ENIAC, comprised 18,000 electron tubes.

In contemporary times, everyday mobile phone chips integrate tens of billions of transistors. In the realm of DNA computing, the current effective scope revolves around addressing problems with a limited number of nodes or variables, utilizing fewer than a few hundred participating DNA strands.

Spatial Separation

Spatial separation involves dividing an entire reaction into distinct compartments. This division restricts molecules from different compartments, preventing them from interacting, enabling efficient execution of reactions within each compartment. Semiconductor circuits and cells employ spatial separation to regulate material and information transmission pathways, facilitating the completion of intricate computing tasks. Similarly, spatial separation is a concept explored in DNA computing.

Advancements in DNA Computing :DNA computer revolutions

In 2011, Chandran et al. introduced a theoretical framework aiming to achieve parallel and scalable computation. This innovative approach utilized localized strand displacement reactions on the surface of DNA nanostructures. Subsequently, in 2016, Genotet al. accomplished the simultaneous observation of 104 reactions.

This was achieved by encapsulating a computational reaction system with diverse input conditions into droplets. The molecules within each droplet reacted independently, facilitated by an oil film that obstructed molecular communication between droplets. This breakthrough allowed for parallel and high-resolution mapping of circuits.

Utilizing Communicative Separation for Chemical Information Storage

The concept of communicative separation enables distinct spatial positions to store varied chemical information while facilitating input/output communication. In 2019, Joesaar et al. achieved a significant advancement by encapsulating basic logic blocks into proteinosomes, essentially creating protocells that mimic the functions of natural cells.

In this innovative approach, the released DNA strands from one protocell, serving as the output of a reaction, could traverse protocell membranes, disperse in the solution, and subsequently enter another protocell. This process effectively triggered downstream reactions, acting as input strands for the subsequent phase.

Integration of Order and Disorder

The collision events of DNA molecules in a solution exhibit a degree of disorder, introducing a notable level of parallelism to DNA computation along with a certain degree of inaccuracy. This parallelism involves subdividing a deterministic space into a probability space for a given calculation. To illustrate, consider the search algorithm: in sequential computing, each exploration of a potential path results in the generation of a specific output.

Parallel Exploration in DNA Molecular Reactions

In parallel DNA molecular reactions, all conceivable paths are explored simultaneously. As the multitude of potential reaction paths grows, the need for detectors with heightened sensitivity and accuracy becomes imperative to derive solutions for given problems. Moreover, with an increasing number of molecules in the system, the likelihood of a single molecule engaging in non-specific binding states rises. This, in turn, can diminish the speed and probability along the correct reaction path while elevating the probability of signal leakage.

Reversibility and Directionality in Reactions

Presently, the generate-and-test approach stands as the predominant method for experimentally showcasing the DNA computing process. However, when the scale of potential solutions surpasses the quantities of available molecules, the problem becomes theoretically unfeasible. Moreover, the faithful readout of results is constrained by the proportion of correct calculation outcomes.

Efficient DNA Assembly for Problem Solutions

Conceptualizing a solution to a problem involves the correct assembly of DNA molecules, and achieving a high yield in the correct DNA assembly is advantageous for filtering the correct answer. In instances where the yield is excessively low, a problem that is solvable may be mistakenly interpreted as having no solution. Addressing this, Condon and colleagues introduced a strategy employing reversible strand displacement reactions for DNA computations, emphasizing both space and energy efficiency.

Summary

Over the past 30 years, DNA computing has undergone gradual yet consistent evolution. While there have been noteworthy advancements, challenges persist across various aspects, including function diversity, achievable circuit size, and computing efficiency. Notably, DNA computing’s reliance on molecular diffusion and the recognition of DNA molecules distinguishes it fundamentally from conventional and other computing systems utilizing universal signals like electrons or photons.

We anticipate that the future of DNA computing, characterized by molecular intelligence, will draw inspiration from both natural living systems and electronic computers.

The results of molecules produced by the final reaction, which researchers could read by measuring.

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