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computing Real Numbers with Large-Population Protocols Having a Continuum of Equilibria 28

Computing Real Numbers with Large-Population Protocols Havin...

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

作者： Huang, Xiang Huls, Rachel N. Department of Computer Science University of Illinois Springfield United States Department of Mathematics University of Illinois Springfield United States

ISBN: (纸本)9783959772532

Bournez, Fraigniaud, and Koegler [6] defined a number in [0,1] as computable by their Large-Population Protocol (LPP) model, if the proportion of agents in a set of marked states converges to said number over time as the population grows to infinity. the notion, however, restricts the ordinary differential equations (ODEs) associated with an LPP to have only finitely many equilibria. this restriction places an intrinsic limitation on the model. As a result, a number is computable by an LPP if and only if it is algebraic, namely, not a single transcendental number can be computed under this notion. In this paper, we lift the finitary requirement on equilibria. that is, we consider systems with a continuum of equilibria. We show that essentially all numbers in [0,1] that are computable by bounded general-purpose analog computers (GPACs) or chemical reaction networks (CRNs) can also be computed by LPPs under this new definition. this implies a rich series of numbers (e.g., the reciprocal of Euler’s constant, π/4, Euler’s γ, Catalan’s constant, and Dottie number) are all computable by LPPs. Our proof is constructive: We develop an algorithm that transfers bounded GPACs/CRNs into LPPs. Our algorithm also fixes a gap in Bournez et al.’s construction of LPPs designed to compute any arbitrary algebraic number in [0,1]. © Xiang Huang and Rachel N. Huls.

关键词： Analog computers

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Minimum Free Energy, Partition Function and Kinetics Simulation Algorithms for a Multistranded Scaffolded dna Computer 29

Minimum Free Energy, Partition Function and Kinetics Simulat...

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29th international conference on dna computing and molecular programming, dna 2023

作者： Shalaby, Ahmed thachuk, Chris Woods, Damien Hamilton Institute Department of Computer Science Maynooth University Ireland Paul G. Allen School of Computer Science & Engineering University of Washington SeattleWA United States

ISBN: (纸本)9783959772976

Polynomial time dynamic programming algorithms play a crucial role in the design, analysis and engineering of nucleic acid systems including dna computers and dna/RNA nanostructures. However, in complex multistranded or pseudoknotted systems, computing the minimum free energy (MFE), and partition function of nucleic acid systems is NP-hard. Despite this, multistranded and/or pseudoknotted systems represent some of the most utilised and successful systems in the field. this leaves open the tempting possibility that many of the kinds of multistranded and/or pseudoknotted systems we wish to engineer actually fall into restricted classes, that do in fact have polynomial time algorithms, but we've just not found them yet. Here, we give polynomial time algorithms for MFE and partition function calculation for a restricted kind of multistranded system called the 1D scaffolded dna computer. this model of computation thermodynamically favours correct outputs over erroneous states, simulates finite state machines in 1D and Boolean circuits in 2D, and is amenable to dna storage applications. In an effort to begin to ask the question of whether we can naturally compare the expressivity of nucleic acid systems based on the computational complexity of prediction of their preferred energetic states, we show our MFE problem is in logspace (the complexity class L), making it perhaps one of the simplest known, natural, nucleic acid MFE problems. Finally, we provide a stochastic kinetic simulator for the 1D scaffolded dna computer and evaluate strategies for efficiently speeding up this thermodynamically favourable system in a constant-temperature kinetic regime. © Ahmed Shalaby, Chris thachuk, and Damien Woods;licensed under Creative Commons License CC-BY 4.0.

关键词： dna

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Accelerating Phylogeny-Aware Short dna Read Alignment with FPGAs

Accelerating Phylogeny-Aware Short DNA Read Alignment with F...

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Annual IEEE Symposium on Field-Programmable Custom computing Machines (FCCM)

作者： Nikolaos Alachiotis Simon A. Berger Alexandros Stamatakis Exelixis Laboratory Scientific Computing Group Heidelberg Institute for Theoretical Studies Heidelberg Germany

Recent advances in molecular sequencing technology have given rise to novel algorithms for simultaneously aligning short sequence reads to reference sequence alignments and corresponding evolutionary reference trees. We present a complete hardware/software implementation for the acceleration of a program called PaPaRa, a newly introduced dynamic programming algorithm for this purpose. We verify the correctness of the proposed architecture on a real FPGA and introduce a straight-forward communication protocol(using gigabit ethernet) for seamless integration with the encapsulating steering software that is executed on a PC processor. the hardware description and the software implementation are freely available for download. When mapped to a Virtex 6 FPGA, our reconfigurable architecture can compute 133.4 billion cell updates per second for the novel, tree-based alignment kernel of PaPaRa. Compared to PaPaRa, running on a 3.2GHz Intel Core i5 CPU, we obtain speedups for the alignment kernel, that range between 170 and 471. For the entire application, that is, the alignment kernel and the trace-back step, we obtain speedups between 74 and 118.

关键词： Field programmable gate arrays Computer architecture Phylogeny Kernel Microprocessors Dynamic programming Acceleration

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ALCH: An imperative language for chemical reaction network-controlled tile assembly 26

ALCH: An imperative language for chemical reaction network-c...

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

作者： Klinge, Titus H. Lathrop, James I. Moreno, Sonia Potter, Hugh D. Raman, Narun K. Riley, Matthew R. Department of Mathematics and Computer Science Drake University Des MoinesIA United States Department of Computer Science Iowa State University AmesIA United States Department of Computer Science Carleton College NorthfieldMN United States

ISBN: (纸本)9783959771634

In 2015 Schiefer and Winfree introduced the chemical reaction network-controlled tile assembly model (CRN-TAM), a variant of the abstract tile assembly model (aTAM), where tile reactions are mediated via non-local chemical signals. In this paper, we introduce ALCH, an imperative programming language for specifying CRN-TAM programs. ALCH contains common features like Boolean variables, conditionals, and loops. It also supports CRN-TAM-specific features such as adding and removing tiles. A unique feature of the language is the branch statement, a nondeterministic control structure that allows us to query the current state of tile assemblies. We also developed a compiler that translates ALCH to the CRN-TAM, and a simulator that simulates and visualizes the self-assembly of a CRN-TAM program. Using this language, we show that the discrete Sierpinski triangle can be strictly self-assembled in the CRN-TAM. this solves an open problem that the CRN-TAM is capable of self-assembling infinite shapes at scale one that the aTAM cannot. ALCH allows us to present this construction at a high level, abstracting species and reactions into C-like code that is simpler to understand. Our construction utilizes two new CRN-TAM techniques that allow us to tackle this open problem. First, it employs the branching feature of ALCH to probe the previously placed tiles of the assembly and detect the presence and absence of tiles. Second, it uses scaffolding tiles to precisely control tile placement by occluding any undesired binding sites. © Titus H. Klinge, James I. Lathrop, Sonia Moreno, Hugh D. Potter, Narun K. Raman, and Matthew R. Riley

关键词： C (programming language)

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New methods for detecting lineage-specific selection

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10th Annual international conference on Research in Computational molecular Biology

作者： Siepel, Adam Pollard, Katherine S. Haussler, David Univ Calif Santa Cruz Ctr Biomol Sci & Engn Santa Cruz CA 95064 USA Univ Calif Santa Cruz Howard Hughes Med Inst Santa Cruz CA 95064 USA

ISBN: (纸本)3540332952

So far, most methods for identifying sequences tinder selection based on comparative sequence data have either assumed selectional pressures are the same across all branches of a phylogeny, or have focused on changes in specific lineages of interest. Here, we introduce a more general method that detects sequences that have either come under selection, or begun to drift, on any lineage. the method is based on a phylogenetic hidden Markov model (phylo-HMM), and does not require element boundaries to be determined a prion, making it particularly useful for identifying noncoding sequences. Insertions and deletions (indels) are incorporated into the phylo-HMM by a simple strategy that uses a separately reconstructed "indel history." To evaluate the statistical significance of predictions, we introduce a novel method for computing P-values based on prior and posterior distributions of the number of substitutions that have occurred in the evolution of predicted elements. We derive efficient dynamic-programming algorithms for obtaining these distributions, given a model of neutral evolution. Our methods have been implemented as computer programs called DLESS (Detection of LinEage-Specific Selection) and phyloP (phylogenetic P-values). We discuss results obtained with these programs on both real and simulated data sets.

关键词： dna sequences

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Tetracycline Intelligent Target-Inducing Logic Gate Based on Triple-Stranded dna Nanoswitch 16th

Tetracycline Intelligent Target-Inducing Logic Gate Based on...

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16th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2021

作者： Xi, Sunfan Wang, Yue Hu, Mengyang Wang, Luhui Cheng, Meng Dong, Yafei College of Life Science Shaanxi Normal University Shaanxi Xi’an710119 China School of Computer Science Shaanxi Normal University Shaanxi Xi’an710119 China

ISBN: (纸本)9789811912559

A previously unreported three-strand dna (ts-dna) non-metal structure with hairpin structure was designed based on a strategy of logic switching and tetracycline (TC) signaling molecule switching. Will target and TC-binding aptamer (TBA) is the combination of body, and its relation with three functional chain dna conformation, with programmable dna sensor signal by FAM input molecule fluorescence emission monitoring. After the combination, the input signal is converted to a fluorescent signal to perform a logical operation. By introducing a novel nanomaterial, graphene oxide (GO), as a signal regulator, the fluorescence response changed by intermolecular interactions is the key to achieving logical calculation. the harm of tetracycline can generally cause kidney damage, ear damage, gastrointestinal adverse reactions, skin allergies, *** tetracycline as a molecular trigger to induce conformational changes in dna, a logical operation target detection method was constructed. In addition, nanoscale devices can be reconfigured and optimized to accommodate additional logical calculations and target detection. © 2022, Springer Nature Singapore Pte Ltd.

关键词： dna

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Efficient Parameter Estimation for dna Kinetics Modeled as Continuous-Time Markov Chains 1

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

作者： Zolaktaf, Sedigheh Dannenberg, Frits Winfree, Erik Bouchard-CÃ´tÃ©, Alexandre Schmidt, Mark Condon, Anne University of British Columbia VancouverBC Canada California Institute of Technology PasadenaCA United States

ISBN: (数字)9783030268077

ISBN: (纸本)9783030268060

Nucleic acid kinetic simulators aim to predict the kinetics of interacting nucleic acid strands. Many simulators model the kinetics of interacting nucleic acid strands as continuous-time Markov chains (CTMCs). States of the CTMCs represent a collection of secondary structures, and transitions between the states correspond to the forming or breaking of base pairs and are determined by a nucleic acid kinetic model. the number of states these CTMCs can form may be exponentially large in the length of the strands, making two important tasks challenging, namely, mean first passage time (MFPT) estimation and parameter estimation for kinetic models based on MFPTs. Gillespieâ€™s stochastic simulation algorithm (SSA) is widely used to analyze nucleic acid folding kinetics, but could be computationally expensive for reactions whose CTMC has a large state space or for slow reactions. It could also be expensive for arbitrary parameter sets that occur in parameter estimation. Our work addresses these two challenging tasks, in the full state space of all non-pseudoknotted secondary structures of each reaction. In the first task, we show how to use a reduced variance stochastic simulation algorithm (RVSSA), which is adapted from SSA, to estimate the MFPT of a reactionâ€™s CTMC. In the second task, we estimate model parameters based on MFPTs. To this end, first, we show how to use a generalized method of moments (GMM) approach, where we minimize a squared norm of moment functions that we formulate based on experimental and estimated MFPTs. Second, to speed up parameter estimation, we introduce a fixed path ensemble inference (FPEI) approach, that we adapt from RVSSA. We implement and evaluate RVSSA and FPEI using the Multistrand kinetic simulator. In our experiments on a dataset of dna reactions, FPEI speeds up parameter estimation compared to inference using SSA, by more than a factor of three for slow reactions. Also, for reactions with large state spaces, it speeds up parameter

关键词： Stochastic systems

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Multithreaded Parallel Sequence Alignment Based on Needleman-Wunsch Algorithm

Multithreaded Parallel Sequence Alignment Based on Needleman...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Veska Gancheva Ivaylo Georgiev Department of Programming and Computer Technology Technical University of Sofia Sofia Bulgaria The Stephan Angeloff Institute of Microbiology Sofia Bulgaria

ISBN: (纸本)9781728146188

Biocomputing and molecular biology are areas that change knowledge and skills for acquisition, storing, management, analysis, interpretation and dissemination of biological information. this requires the utilization of high performance computers and innovative software tools for management of the vast information, as well as deployment of innovative algorithmic techniques for analysis, interpretation and prognostication of data in order to get to insight of the design and validation of life-science experiments. Sequence alignment is an important method in dna and protein analysis. the paper describes the computational challenges in biological sequence processing. the great challenges are to propose parallel computational models and parallel program implementations based on the algorithms for biological sequence alignment. An investigation of the efficiency of sequence alignment based on parallel multithreaded program implementation of Needleman-Wunsch algorithm is presented in this paper. Parallel computational model based on Needleman-Wunsch algorithm is designed. the proposed parallel model is verified by multithreaded parallel program implementation utilizing OpenMP. A number of experiments have been carried out for the case of various data sets and a various number of threads. Parallel performance parameters execution time and speedup are estimated experimentally. the performance estimation and scalability analyses show that the suggested model has good scalability both in respect to the workload and machine size.

关键词： Heuristic algorithms Proteins Computational modeling Dynamic programming Bioinformatics Software algorithms

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Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic Hardness and Parameterized Bounds 30

Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic H...

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

作者： Demaine, Erik D. Gomez, Timothy Grizzell, Elise Hecher, Markus Lynch, Jayson Schweller, Robert Shalaby, Ahmed Woods, Damien Massachusetts Institute of Technology United States University of Texas Rio Grande Valley United States Hamilton Institute Department of Computer Science Maynooth University Ireland

ISBN: (纸本)9783959773447

molecular programmers and nanostructure engineers use domain-level design to abstract away messy dna/RNA sequence, chemical and geometric details. Such domain-level abstractions are enforced by sequence design principles and provide a key principle that allows scaling up of complex multistranded dna/RNA programs and structures. Determining the most favoured secondary structure, or Minimum Free Energy (MFE), of a set of strands, is typically studied at the sequence level but has seen limited domain-level work. We analyse the computational complexity of MFE for multistranded systems in a simple setting were we allow only 1 or 2 domains per strand. On the one hand, with 2-domain strands, we find that the MFE decision problem is NP-complete, even without pseudoknots, and requires exponential time algorithms assuming SAT does. On the other hand, in the simplest case of 1-domain strands there are efficient MFE algorithms for various binding modes. However, even in this single-domain case, MFE is P-hard for promiscuous binding, where one domain may bind to multiple as experimentally used by Nikitin [Nat Chem., 2023], which in turn implies that strands consisting of a single domain efficiently implement arbitrary Boolean circuits. © Erik D. Demaine, Timothy Gomez, Elise Grizzell, Markus Hecher, Jayson Lynch, Robert Schweller, Ahmed Shalaby, and Damien Woods

关键词： Domain-based dna designs efficient algorithms fixed-parameter tractable minimum free energy NC NP-hard P-hard

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Accelerating Self-Assembly of Crisscross Slat Systems 29

Accelerating Self-Assembly of Crisscross Slat Systems

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29th international conference on dna computing and molecular programming, dna 2023

作者： Doty, David Fleming, Hunter Hader, Daniel Patitz, Matthew J. Vaughan, Lukas A. University of California DavisCA United States University of Arkansas FayettevilleAR United States

ISBN: (纸本)9783959772976

We present an abstract model of self-assembly of systems composed of "crisscross slats", which have been experimentally implemented as a single-stranded piece of dna [21] or as a complete dna origami structure [28]. We then introduce a more physically realistic "kinetic" model and show how important constants in the model were derived and tuned, and compare simulation-based results to experimental results [21,28]. Using these models, we show how we can apply optimizations to designs of slat systems in order to lower the numbers of unique slat types required to build target structures. In general, we apply two types of techniques to achieve greatly reduced numbers of slat types. Similar to the experimental work implementing dna origami-based slats, in our designs the slats oriented in horizontal and vertical directions are each restricted to their own plane and sets of them overlap each other in square regions which we refer to as macrotiles. Our first technique extends their previous work of reusing slat types within macrotiles and requires analyses of binding domain patterns to determine the potential for errors consisting of incorrect slat types attaching at undesired translations and reflections. the second technique leverages the power of algorithmic self-assembly to efficiently reuse entire macrotiles which self-assemble in patterns following designed algorithms that dictate the dimensions and patterns of growth. Using these designs, we demonstrate that in kinetic simulations the systems with reduced numbers of slat types self-assemble more quickly than those with greater numbers. this provides evidence that such optimizations will also result in greater assembly speeds in experimental systems. Furthermore, the reduced numbers of slat types required have the potential to vastly reduce the cost and number of lab steps for crisscross assembly experiments. © David Doty, Hunter Fleming, Daniel Hader, Matthew J. Patitz, and Lukas A. Vaughan;licensed under Creative C

关键词： dna

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