the proceedings contain 11 papers. the topics discussed include: the topology of scaffold routings on non-spherical mesh wireframe;simplifying chemical reaction network implementations with two-stranded dna building b...
ISBN:
(纸本)9783959771634
the proceedings contain 11 papers. the topics discussed include: the topology of scaffold routings on non-spherical mesh wireframe;simplifying chemical reaction network implementations with two-stranded dna building blocks;composable computation in leaderless, discrete chemical reaction networks;CRNs exposed: a method for the systematic exploration of chemical reaction networks;population-induced phase transitions and the verification of chemical reaction networks;ALCH: an imperative language for chemical reaction network-controlled tile assembly;implementing non-equilibrium networks with active circuits of duplex catalysts;design automation of polyomino set that self-assembles into a desired shape;verification and computation in restricted tile automata;and turning machines.
the proceedings contain 11 papers. the topics discussed include: Turing universality of step-wise and stage assembly at temperature 1;a type system for dnaQL;deterministic function computation with chemical reaction n...
ISBN:
(纸本)9783642322075
the proceedings contain 11 papers. the topics discussed include: Turing universality of step-wise and stage assembly at temperature 1;a type system for dnaQL;deterministic function computation with chemical reaction networks;reachability bounds for chemical reaction networks and strand displacement systems;synthesizing minimal tile sets for complex patterns in the framework of patterned dna self-assembly;a geometric approach to Gibbs energy landscapes and optimal dna codeword design;a dna based molecular logic gate capable of a variety of logical operations;deciding whether a regular language is generated by a splicing system;probabilistic reasoning with a Bayesian dna device based on strand displacement;dna self-assembly and computation studied with a coarse-grained dynamic bonded model;and space and energy efficient computation withdna strand displacement systems.
the proceedings contain 16 papers. the topics discussed include: filter position in networks of evolutionary processors does not matter: a direct proof;strand algebras for dnacomputing;a domain-specific language for ...
ISBN:
(纸本)364210603X
the proceedings contain 16 papers. the topics discussed include: filter position in networks of evolutionary processors does not matter: a direct proof;strand algebras for dnacomputing;a domain-specific language for programming in the tile assembly model;advancing the deoxyribozyme-based logic gate design process;dna chips for species identification and biological phylogenies;renewable, time-responsive dna logic gates for scalable digital circuits;self-assembly of the discrete Sierpinski carpet and related fractals;automatic design of dna logic gates based on kinetic simulation;design of a biomolecular device that executes process algebra;the effect of malformed tiles on tile assemblies within kTAM;positional state representation and its transition control for photonic dna automation;construction of AND gate for RTRACS withthe capacity of extension to NAND gate;and time-complexity of multilayered dna strand displacement circuits.
the proceedings contain 16 papers. the topics discussed include: improving efficiency of 3-SAT-solving tile systems;optimizing tile concentrations to minimize errors and time for dna tile self-assembly systems;scalabl...
ISBN:
(纸本)9783642183041
the proceedings contain 16 papers. the topics discussed include: improving efficiency of 3-SAT-solving tile systems;optimizing tile concentrations to minimize errors and time for dna tile self-assembly systems;scalable, time-responsive, digital, energy-efficient molecular circuits using dna strand displacement;negative interactions in irreversible self-assembly;search and validation of short genome-wide biomarkers for bacterial biological phylogenies;high-fidelity dna hybridization using programmable moleculardna devices;synthesizing minimal tile sets for patterned dna self-assembly;operation of a dna-based autocatalytic network in serum;triangular tile self-assembly systems;randomized self assembly of rectangular nano structures;design of a functional nanomaterial with recognition ability for constructing light-driven nanodevices;efficient Turing-universal computation withdna polymers;and simple evolution of complex crystal species.
Empirical modeling, which is a process of developing a mathematical model of a system from experimental data, has attracted many researchers due to its wide applicability. Finding boththe structure and appropriate nu...
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Empirical modeling, which is a process of developing a mathematical model of a system from experimental data, has attracted many researchers due to its wide applicability. Finding boththe structure and appropriate numeric coefficients of the model is a real challenge. Genetic programming (GP) has been applied by many practitioners to solve this problem. However, there are a number of issues which require careful attention while applying GP to empirical modeling problems. We begin with highlighting the importance of these issues including: computational efforts in evolving a model, premature convergence, generalization ability of an evolved model, building hierarchical models, and constant creation techniques. We survey and classify different approaches used by GP researchers to deal withthe mentioned issues. We present different performance measures which are useful to report the results of analysis of GP runs. We hope this work would help the reader by facilitating to understand key concepts and practical issues of GP and steering in selection of an appropriate approach to solve a particular issue effectively.
We propose a novel molecularcomputing approach based on reservoir computing. In reservoir computing, a dynamical core, called a reservoir, is perturbed with an external input signal while a readout layer maps the res...
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ISBN:
(纸本)9783319019284;9783319019277
We propose a novel molecularcomputing approach based on reservoir computing. In reservoir computing, a dynamical core, called a reservoir, is perturbed with an external input signal while a readout layer maps the reservoir dynamics to a target output. Computation takes place as a transformation from the input space to a high-dimensional spatiotemporal feature space created by the transient dynamics of the reservoir. the readout layer then combines these features to produce the target output. We show that coupled deoxyribozyme oscillators can act as the reservoir. We show that despite using only three coupled oscillators, a molecular reservoir computer could achieve 90% accuracy on a benchmark temporal problem.
We study the computational complexity of the recently proposed nubots model of molecular-scale self-assembly. the model generalises asynchronous cellular automata to have non-local movement where large assemblies of m...
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We study the computational complexity of the recently proposed nubots model of molecular-scale self-assembly. the model generalises asynchronous cellular automata to have non-local movement where large assemblies of molecules can be moved around, analogous to millions of molecular motors in animal muscle effecting the rapid movement of macroscale arms and legs. We show that nubots is capable of simulating Boolean circuits of polylogarithmic depth and polynomial size, in only polylogarithmic expected time. In computational complexity terms, we show that any problem from the complexity class NC is solved in polylogarithmic expected time on nubots that use a polynomial amount of workspace. Along the way, we give fast parallel algorithms for a number of problems including line growth, sorting, Boolean matrix multiplication and space-bounded Turing machine simulation, all using a constant number of nubot states (monomer types). Circuit depth is a well-studied notion of parallel time, and our result implies that nubots is a highly parallel model of computation in a formal sense. Asynchronous cellular automata are not capable of such parallelism, and our result shows that adding a movement primitive to such a model, to get the nubots model, drastically increases parallel processing abilities.
dnacomputing is a new method for computation using the technology in molecular biology. the enormous parallel computing ability of dnacomputing brings new opportunities and challenges to the development of cryptogra...
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ISBN:
(纸本)9781479920815
dnacomputing is a new method for computation using the technology in molecular biology. the enormous parallel computing ability of dnacomputing brings new opportunities and challenges to the development of cryptography. dna cryptography is a cutting-edge sciences which combines classical cryptogram and molecularcomputing. Finite field GF(2(n)) is one of the most commonly used mathematic sets for cryptography. this paper proposes a parallel molecularcomputing system to compute the modular-multiplication, an operation combining multiplication and reduction, over finite field GF(2(n)). the operation of reduction is executed after the completion of the operation of multiplication. An instance of computing modular-multiplication is introduced to show the details of our system. the time complexity is theta(n) and the space complexity is theta(n(2)).
Unlike their traditional, silicon counterparts, dna computers have natural interfaces with both chemical and biological systems. these can be used for a number of applications, including the precise arrangement of mat...
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Unlike their traditional, silicon counterparts, dna computers have natural interfaces with both chemical and biological systems. these can be used for a number of applications, including the precise arrangement of matter at the nanoscale and the creation of smart biosensors. Like silicon circuits, dna strand displacement systems (DSD) can evaluate non-trivial functions. However, these systems can be slow and are susceptible to errors. It has been suggested that localised hybridization reactions could overcome some of these challenges. Localised reactions occur in dna 'walker' systems which were recently shown to be capable of navigating a programmable track tethered to an origami tile. We investigate the computational potential of these systems for evaluating Boolean functions and forming composable circuits. We find that systems of multiple walkers have severely limited potential for parallel circuit evaluation. dna walkers, like DSDs, are also susceptible to errors. We develop a discrete stochastic model of dna walker 'circuits' based on experimental data, and demonstrate the merit of using probabilistic model checking techniques to analyse their reliability, performance and correctness. this analysis aids in the design of reliable and efficient dna walker circuits.
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