Mesoscopic computer engineering: Automating
                    DNA-based molecular computing via traditional
                    practices of parallel computer architecture
                    design

Amenyo, John-Thones

doi:10.1090/dimacs/044/11

Cited by 4 publications

(2 citation statements)

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“…They could do make graph optimization on molecular level. Amenyo [37] showed that all proposed DNA computing algorithms can be run on parallel computer architectures configured from trellis/lattice banks, filter banks and switching banks. Thus, DNA computation can be re-interpreted as dataflow (or signal flow) networks and subject to conventional …”

Section: Dna Computation Systemsmentioning

confidence: 99%

Another expert system rule inference based on DNA molecule logic gates

Wasiewicz

2013

Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013

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With the help of silicon industry microfluidic processors were invented utilizing nano membrane valves, pumps and microreactors. These so called lab-on-a-chips combined together with molecular computing create molecular-systems-ona-chips. This work presents a new approach to implementation of molecular inference systems. It requires the unique representation of signals by DNA molecules. The main part of this work includes the concept of logic gates based on typical genetic engineering reactions. The presented method allows for constructing logic gates with many inputs and for executing them at the same quantity of elementary operations, regardless of a number of input signals. Every microreactor of the lab-on-a-chip performs one unique operation on input molecules and can be connected by dataflow output-input connections to other ones.

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Section: Dna Computation Systemsmentioning

confidence: 99%

Another expert system rule inference based on DNA molecule logic gates

Wasiewicz

2013

Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013

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show abstract

“…They could do make graph optimization on molecular level. Amenyo [3] showed that all proposed DNA computing algorithms can be run on parallel computer architectures configured from trellis/lattice banks, filter banks and switching banks. Thus, DNA computation can be re-interpreted as dataflow (or signal flow) networks and subject to conventional treatment.…”

Section: More Advanced Techniques Of Computing On Moleculesmentioning

confidence: 99%

<title>Enzyme optimization for next level molecular computing</title>

Wasiewicz¹,

Malinowski²,

Płucienniczak

2006

SPIE Proceedings

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The main concept of molecular computing depends on DNA self-assembly abilities and on modifying DNA with the help of enzymes during genetic operations. In the typical DNA computing a sequence of operations executed on DNA strings in parallel is called an algorithm, which is also determined by a model of DNA strings. This methodology is similar to the soft hardware specialized architecture driven here by heating, cooling and enzymes, especially polymerases used for copying strings. As it is described in this paper the polymerase Taq properties are changed by modifying its DNA sequence in such a way that polymerase side activities together with peptide chains, responsible for destroying amplified strings, are cut off. Thus, it introduces the next level of molecular computing. The genetic operation execution succession and the given molecule model with designed nucleotide sequences produce computation results and additionally they modify enzymes, which directly influence on the computation process. The information flow begins to circulate. Additionally, such optimized enzymes are more suitable for nanoconstruction, because they have only desired characteristics. The experiment was proposed to confirm the possibilities of the suggested implementation.

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Local parallel biomolecular computation

Reif¹

1999

DNA Based Computers III

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Biomolecular ComputationBMC is computation at the molecular scale, using biotechnology engineering techniques. Most proposed methods for BMC used distributed molecular parallelism DP; where operations are executed in parallel on large numbers of distinct molecules. BMC done exclusively by DP requires that the computation execute sequentially within any given molecule though done in parallel for multiple molecules. In contrast, local parallelism LP allows operations to be executed in parallel on each given molecule.Winfree, et al W96, WYS96 proposed an innovative method for LP-BMC, that of computation by unmediated self-assembly of 2D arrays of DNA molecules, applying known domino tiling techniques see Buchi B62 , Berger B66 , and R71, LP81 in combination with recombinant DNA nano-fabrication techniques of Seeman et al SZC94 . The likelihood for successful unmediated self-assembly of computations has not been determined we discuss a simple model of assembly where there may be blockages in self-assembly, but more sophisticated models may have a higher likelihood of success.We develop improved techniques to more fully exploit the potential power of LP-BMC. To increase the likelihood of success of assembly, w e propose instead a re ned step-wise assembly method, which provides control of the assembly in distinct steps. It does not require large volumes or convergence time, even in the worst case assembly model that we assume for our own assembly algorithms. We also introduce the assembly frame, a rigid nano-structure which binds the input DNA strands in place on its boundaries and constrains the shape of the assembly. Our main results are LP-BMC algorithms for some fundamental problems that form the basis of many parallel computations. For these problems we decrease the assembly size to linear in the input size and and signi cantly decrease the number of time steps. We give LP-BMC algorithms with linear assembly size and logarithmic time, for the parallel pre x computation problems, which include integer addition, subtraction, multiplication by a constant number, nite state automata simulation, and ngerprinting hashing a string. We also give LP-BMC methods for perfect shu e and pair-wise exchange using a linear size assembly and constant time. This provides logarithmic time LP-BMC algorithms for the large class of normal parallel algorithms S71, U84, L92 on shu e-exchange networks, e.g. DFT, bitonic merge, xed permutation of data, as well as evaluation of a bounded degree Boolean circuit in time bounded by a logarithmic times the circuit depth. Our LP-BMC methods require much smaller volumes than previous DP-BMC algorithms R95,R98b, OR97 for these problems. All our LP-BMC assembly techniques can be combined with DP-BMC parallelism to simultaneously solve multiple problems with distinct inputs e.g. do parallel arithmetic on multiple inputs, or determine satisfying inputs of a circuit, so they are an enhancement of the power of DP-BMC.

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Mesoscopic computer engineering: Automating DNA-based molecular computing via traditional practices of parallel computer architecture design

Cited by 4 publications

References 0 publications

Another expert system rule inference based on DNA molecule logic gates

Another expert system rule inference based on DNA molecule logic gates

<title>Enzyme optimization for next level molecular computing</title>

Local parallel biomolecular computation

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