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SIMD||dna: Single Instruction, Multiple Data Computation with dna Strand Displacement Cascades 1

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25th international conference on dna computing and molecular programming, dna 2019

作者： Wang, Boya Chalk, Cameron Soloveichik, David The University of Texas at Austin Austin United States

ISBN: (数字)9783030268077

ISBN: (纸本)9783030268060

Typical dna storage schemes do not allow in-memory computation, and instead transformation of the stored data requires dna sequencing, electronic computation of the transformation, followed by synthesizing new dna. In contrast we propose a model of in-memory computation that avoids the time consuming and expensive sequencing and synthesis steps, with computation carried out by dna strand displacement. We demonstrate the flexibility of our approach by developing schemes for massively parallel binary counting and elementary cellular automaton Rule 110 computation. © 2019, Springer Nature Switzerland AG.

关键词： dna

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A type system for dnaQL

A type system for DNAQL

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18th international conference on dna computing and molecular programming, dna 18

作者： Brijder, Robert Gillis, Joris J. M. Van Den Bussche, Jan Hasselt University Belgium University of Limburg Belgium

ISBN: (纸本)9783642322075

Recently we have introduced a formal graph-based data model for dna complexes geared towards database applications. the model is accompanied by the programming language dnaQL for querying databases in dna. Due to natural restrictions on the implementability and termination of operations on dna, programs in dnaQL are not always well defined on all possible inputs. Indeed, a problem left open by our previous work has been to devise a type system for dnaQL, with a soundness property to the effect that well-typed programs are well defined on all inputs adhering to given input types. the contribution of the present paper is to propose such a type system and to establish soundness. Moreover, we show that the type system is flexible enough so that any database manipulation expressible in the relational algebra is also expressible in dnaQL in a well-typed manner. © 2012 Springer-Verlag.

关键词： dna

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Grammar-based immune programming

Grammar-based immune programming

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15th international conference on dna computing and molecular programming

作者： Bernardino, Heder S. Barbosa, Helio J. C. Lab Nacl Computacao Cient BR-25651075 Petropolis RJ Brazil

this paper describes Grammar-based Immune programming (GIP) for evolving programs in an arbitrary language by immunological inspiration. GIP is based on Grammatical Evolution (GE) in which a grammar is used to define a language and decode candidate solutions to a valid representation (program). However, by default, GE uses a Genetic Algorithm in the search process while GIP uses an artificial immune system. Some modifications are needed of an immune algorithm to use a grammar in order to efficiently decode antibodies into programs. Experiments are performed to analyze algorithm behavior over different aspects and compare it with GEVA, a well known GE implementation. the methods are applied to identify a causal model (an ordinary differential equation) from an observed data set, to symbolically regress an iterated function f(f(x)) = g(x), and to find a symbolic representation of a discontinuous function.

关键词： Artificial immune system Grammatical evolution Immune programming Symbolic regression Model inference

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Prediction Nucleic Acid Secondary Structure with Planar Pseudoknots and Genetic Algorithm 9

Prediction Nucleic Acid Secondary Structure with Planar Pseu...

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9th international conference on Bio-Inspired computing - theories and Applications (BIC-TA)

作者： Zhang, Kai Huang, Xinquan Hu, Wei Liu, Jun Wuhan Univ Sci & Technol Sch Comp Sci Wuhan 430081 Peoples R China

ISBN: (纸本)9783662450482

In recent years, dna and RNA molecules have shown great potential as a design medium for the construction of nanostructures and the programmed assembly of molecular computing. In this paper, we propose a novel genetic algorithm to predict nucleic acid secondary structure with planar pseudoknots. In our algorithm, the free energy and the number of continues base pairs stacking are used as fitness function to evaluate the individuals. We have compared the results obtained by our algorithm with RNAStructure. As will be discussed, our algorithm can efficiently predict the planar pseudoknots with lower free energy and more continues base pairs stacking.

关键词： Secondary structure prediction Genetic algorithm Minimum free energy Dynamic programming Pseudoknots

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Simplifying chemical reaction network implementations with two-stranded dna building blocks 26

Simplifying chemical reaction network implementations with t...

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26th international conference on dna computing and molecular programming, dna 2020

作者： Johnson, Robert F. Qian, Lulu California Institute of Technology PasadenaCA United States

ISBN: (纸本)9783959771634

In molecular programming, the Chemical Reaction Network model is often used to describe real or hypothetical systems. Often, an interesting computational task can be done with a known hypothetical Chemical Reaction Network, but often such networks have no known physical implementation. One of the important breakthroughs in the field was that any Chemical Reaction Network can be physically implemented, approximately, using dna strand displacement mechanisms. this allows us to treat the Chemical Reaction Network model as a programming language and the implementation schemes as its compiler. this also suggests that it would be useful to optimize the result of such a compilation, and in general to find effective ways to design better dna strand displacement systems. We discuss dna strand displacement systems in terms of "motifs", short sequences of elementary dna strand displacement reactions. We argue that describing such motifs in terms of their inputs and outputs, then building larger systems out of the abstracted motifs, can be an efficient way of designing dna strand displacement systems. We discuss four previously studied motifs in this abstracted way, and present a new motif based on cooperative 4-way strand exchange. We then show how Chemical Reaction Network implementations can be built out of abstracted motifs, discussing existing implementations as well as presenting two new implementations based on 4-way strand exchange, one of which uses the new cooperative motif. the new implementations both have two desirable properties not found in existing implementations, namely both use only at most 2-stranded dna complexes for signal and fuel complexes and both are physically reversible. there are reasons to believe that those properties may make them more robust and energy-efficient, but at the expense of using more fuel complexes than existing implementation schemes. © Robert F. Johnson and Lulu Qian;licensed under Creative Commons License CC-BY.

关键词： dna

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Geometric Enumeration of Localized dna Strand Displacement Reaction Networks 30

Geometric Enumeration of Localized DNA Strand Displacement R...

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30th international conference on dna computing and molecular programming, dna 30 2024

作者： Lakin, Matthew R. Kumar, Sarika Department of Computer Science University of New Mexico United States Department of Chemical & Biological Engineering University of New Mexico United States Center for Biomedical Engineering University of New Mexico United States

ISBN: (纸本)9783959773447

Localized molecular devices are a powerful tool for engineering complex information-processing circuits and molecular robots. their practical advantages include speed and scalability of interactions between components tethered near to each other on an underlying nanostructure, and the ability to restrict interactions between more distant components. the latter is a critical feature that must be factored into computational tools for the design and simulation of localized molecular devices: unlike in solution-phase systems, the geometries of molecular interactions must be accounted for when attempting to determine the network of possible reactions in a tethered molecular system. this work aims to address that challenge by integrating, for the first time, automated approaches to analysis of molecular geometry with reaction enumeration algorithms for dna strand displacement reaction networks that can be applied to tethered molecular systems. By adapting a simple approach to solving the biophysical constraints inherent in molecular interactions to be applicable to tethered systems, we produce a localized reaction enumeration system that enhances previous approaches to reaction enumeration in tethered system by not requiring users to explicitly specify the subsets of components that are capable of interacting. this greatly simplifies the user’s task and could also be used as the basis of future systems for automated placement or routing of signal-transmission and logical processing in molecular devices. We apply this system to several published example systems from the literature, including both tethered molecular logic systems and molecular robots. © Matthew R. Lakin and Sarika Kumar

关键词： molecular docking

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9th international conference on Bio-Inspired computing - theories and Applications, BIC-TA 2014

9th International Conference on Bio-Inspired Computing - The...

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9th international conference on Bio-Inspired computing - theories and Applications, BIC-TA 2014

ISBN: (纸本)9783662450482

the proceedings contain 109 papers. the special focus in this conference is on Bio-Inspired computing. the topics include: the application of spiking neural P systems for PLC programming;molecular model for information addressing and transporting based on dna nanotechnology;real-coded genetic algorithm with oriented search towards promising region for parameter optimization;the algorithms and composition of a travel system based on geographical information;using support vector machine to identify imaging biomarkers of major depressive disorder and anxious depression;an adaptive differential evolution algorithm with automatic population resizing for global numerical optimization;an improved method of dna information encryption;an encryption scheme based on dna microdots technology;research on improved locally linear embedding algorithm;an improved evolutionary approach for association rules mining;multiple depots incomplete open vehicle routing problem based on carbon tax;on the convergence of Levenberg Marquardt method for solving nonlinear systems;locate multiple Pareto optima using a species-based multi-objective genetic algorithm;research for performance evaluation of university teachers;an edge detection algorithm based on morphological gradient and the Otsu method;solving the multiobjective multiple traveling salesmen problem using membrane algorithm;a novel method to derive ambulatory blood pressure from the radial pressure waveform;adaptive mutation behavior for quantum particle swarm optimization;bifurcation and global synchronization analysis in diffusively coupled calcium oscillators and uniform solution to partition problem using P systems with membrane division.

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Analyzing Support Vector Machine Overfitting on Microarray Data

Analyzing Support Vector Machine Overfitting on Microarray D...

引用

10th international conference on Intelligent computing (ICIC)

作者： Han, Henry Fordham Univ Dept Comp & Informat Sci New York NY 10458 USA

ISBN: (纸本)9783319093307;9783319093291

Support vector machines (SVM) are a widely used state-of-the-art classifier in molecular diagnostics. However, there is little work done on its overfitting analysis to avoid deceptive diagnostic results. In this work, we investigate the important problem and prove that a SVM classifier would inevitably encounter overfitting for gene expression array data under a standard Gaussian kernel due to the built-in large data variations from dna amplification mechanism in the transcriptional profiling. We have found that SVM demonstrates its own special overfitting characteristics on array data, in addition to showing that feature selection algorithms may not contribute to overcoming overfitting, and discussing overfitting in biomarker discovery algorithm.

关键词： Support vector machines Overfitting dna amplification Biomarker

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A Coupled Reconfiguration Mechanism for Single-Stranded dna Strand Displacement Systems 28

A Coupled Reconfiguration Mechanism for Single-Stranded DNA ...

引用

28th international conference on dna computing and molecular programming, dna 2022

作者： Johnson, Hope Amber Condon, Anne The University of British Columbia Vancouver Canada

ISBN: (纸本)9783959772532

dna Strand Displacement (DSD) systems model basic reaction rules, such as toehold-mediated strand displacement and 4-way branch migration, that modify complexes of bound dna strands. DSD systems have been widely used to design and reason about the correctness of molecular programs, including implementations of logic circuits, neural networks, and Chemical Reaction Networks. Such implementations employ a valuable toolkit of mechanisms – sequences of basic reaction rules – that achieve catalysis, reduce errors (e.g., due to leak), or simulate simple computational units such as logic gates, both in solution and on surfaces. Expanding the DSD toolkit of DSD mechanisms can lead to new and better ways of programming with dna. Here we introduce a new mechanism, which we call controlled reconfiguration. We describe one example where two single-stranded DSD complexes interact, changing the bonds in both complexes in a way that would not be possible for each independently on its own via the basic reaction rules allowed by the model. We use coupled reconfiguration to refer to instances of controlled reconfiguration in which two reactants change each other in this way. We note that our DSD model disallows pseudoknots and that properties of our coupled reconfiguration construction rely on this restriction of the model. A key feature of our coupled reconfiguration example, which distinguishes it from mechanisms (such as 3-way strand displacement or 4-way branch migration) that are typically used to implement molecular programs, is that the reactants are single-stranded. Leveraging this feature, we show how to use coupled reconfiguration to implement Chemical Reaction Networks (CRNs), with a DSD system that has both single-stranded signals (which represent the species of the CRN) and single-stranded fuels (which drive the CRN reactions). Our implementation also has other desirable properties;for example it is capable of implementing reversible CRNs and uses just two distinct toeho

关键词： dna

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Robust digital molecular design of binarized neural networks 27

Robust digital molecular design of binarized neural networks

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27th international conference on dna computing and molecular programming, dna 2021

作者： Linder, Johannes Chen, Yuan-Jyue Wong, David Seelig, Georg Ceze, Luis Strauss, Karin University of Washington Paul G. Allen School of Computer Science and Engineering SeattleWA United States Microsoft Research RedmondWA United States University of Washington Department of Bioengineering SeattleWA United States University of Washington Department of Electrical and Computer Engineering SeattleWA United States

ISBN: (纸本)9783959772051

molecular programming - a paradigm wherein molecules are engineered to perform computation - shows great potential for applications in nanotechnology, disease diagnostics and smart therapeutics. A key challenge is to identify systematic approaches for compiling abstract models of computation to molecules. Due to their wide applicability, one of the most useful abstractions to realize is neural networks. In prior work, real-valued weights were achieved by individually controlling the concentrations of the corresponding "weight" molecules. However, large-scale preparation of reactants with precise concentrations quickly becomes intractable. Here, we propose to bypass this fundamental problem using Binarized Neural Networks (BNNs), a model that is highly scalable in a molecular setting due to the small number of distinct weight values. We devise a noise-tolerant digital molecular circuit that compactly implements a majority voting operation on binary-valued inputs to compute the neuron output. the network is also rate-independent, meaning the speed at which individual reactions occur does not affect the computation, further increasing robustness to noise. We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions. Next, we map the reactions to dna strand displacement cascades, providing simulation results that demonstrate the practical feasibility of our approach. We perform extensive noise tolerance simulations, showing that digital molecular neurons are notably more robust to noise in the concentrations of chemical reactants compared to their analog counterparts. Finally, we provide initial experimental results of a single binarized neuron. Our work suggests a solid framework for building even more complex neural network computation. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Neural networks

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