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检索条件"任意字段=17th International Conference on DNA Computing and Molecular Programming, DNA 17"

共 109 条记录，以下是61-70 订阅

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A dna computing system of modular-multiplication over finite field GF(2n)

A DNA computing system of modular-multiplication over finite...

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13th international conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2013

作者： Li, Yongnan Xiao, Limin Ruan, Li Zhang, Zhenzhong Li, Deguo State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computer Science and Engineering Beihang University Beijing 100191 China

ISBN: (纸本)9783319038582

the enormous parallel computing ability and high memory density of dna computing bring potential challenges and opportunities to traditional cryptography. Finite field GF(2n) is one of the most commonly used mathematic sets for cryptography. It is an open problem that how to implement the arithmetic operations over finite field GF(2n) based on dna computing. Existing research has the problem that the lengths of parameters in the dna tile assembly process could not match each other strictly. this paper proposes a parallel molecular computing system to compute the modular-multiplication, an operation combining multiplication and reduction over finite field GF(2n). the multiplication and the reduction are executed simultaneously in this system. One concrete example of 1100 · 1001 mod 10011 is proposed to show the details of our tile assembly system. the time complexity of this system is Θ(n) and the space complexity is Θ(n2). this system requires 210 types of computation tiles and 17 types of boundary tiles. © Springer international Publishing Switzerland 2013.

关键词： Cryptography

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dna-GCN: Graph Convolutional Networks for Predicting dna-Protein Binding 17th

DNA-GCN: Graph Convolutional Networks for Predicting DNA-Pro...

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17th international conference on Intelligent computing, ICIC 2021

作者： Guo, Yuhang Luo, Xiao Chen, Liang Deng, Minghua School of Mathematical Sciences Peking University Beijing China Damo Academy Alibaba Group Hangzhou China

ISBN: (纸本)9783030845315

Predicting dna-protein binding is an important and classic problem in bioinformatics. Convolutional neural networks have outperformed conventional methods in modeling the sequence specificity of dna-protein binding. However, none of the studies has utilized graph convolutional networks for motif inference. In this work, we propose to use graph convolutional networks for motif inference. We build a sequence k-mer graph for the whole dataset based on the k-mer co-occurrence and k-mer sequence relationship and then learn dna Graph Convolutional Network(dna-GCN) for the whole dataset. Our dna-GCN is initialized with a one-hot representation for all nodes, and it then jointly learns the embeddings for both k-mers and sequences, as supervised by the known labels of sequences. We evaluate our model on 50 datasets from ENCODE. dna-GCN shows its competitive performance compared with the baseline model. Besides, we analyze our model and design several different architectures to help fit different datasets. © 2021, Springer Nature Switzerland AG.

关键词： Bioinformatics

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Selection of Characteristics and Classification of dna Microarrays Using Bioinspired Algorithms and the Generalized Neuron 17th

Selection of Characteristics and Classification of DNA Micro...

引用

17th Mexican international conference on Artificial Intelligence (MICAI)

作者： Alejandra Romero-Montiel, Flor Rodriguez-Vazquez, Katya Univ Nacl Autonoma Mexico Inst Invest Matemt Aplicadas & Sistemas IIMAS Mexico City DF Mexico

ISBN: (纸本)9783030044916;9783030044909

dna microarrays are used for the massive quantification of gene expression. this analysis allows to diagnose, identify and classify different diseases. this is a computationally challenging task due to the large number of genes and a relatively small number of samples. Some papers applied the generalized neuron (GN) to solve approximation functions, to calculate density estimates, prediction and classification problems [1,2]. In this work we show how a GN can be used in the task of microarray classification. the proposed methodology is as follows: first reducing the dimensionality of the genes using a genetic algorithm, then the generalized neuron is trained using one bioinspired algorithms: Particle Swarm Optimization, Genetic Algorithm and Differential Evolution. Finally the precision of the methodology it is tested by classifying three databases of dna microarrays: Leukemia benchmarck ALL - AML, Colon Tumor and Prostate cancer.

关键词： Microarrays Genetic algorithms PSO Differential evolution Neural networks Pattern recognition

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Genome-wide survival analysis of somatic mutations in cancer

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17th Annual international conference on Research in Computational molecular Biology, RECOMB 2013

作者： Vandin, Fabio Papoutsaki, Alexandra Raphael, Benjamin J. Upfal, Eli Department of Computer Science Brown University Providence RI United States Center for Computational Molecular Biology Brown University Providence RI United States

ISBN: (纸本)9783642371943

Motivation. Next-generation dna sequencing technologies now enable the measurement of exomes, genomes, and mRNA expression in many samples. the next challenge is to interpret these large quantities of dna and RNA sequence data. In many human and cancer genomics studies, a major goal is to discover associations between an observed phenotype and a particular variable from genome-wide measurements of many such variables. In this work we consider the problem of testing the association between a dna sequence variant and the survival time, or length of time that patients live following diagnosis or treatment. this problem is relevant to many cancer sequencing studies, in which one aims to discover somatic variants that distinguish patients with fast-growing tumors that require aggressive treatment from patients with better prognosis [1]. © 2013 Springer-Verlag.

关键词： dna sequences

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dna-Binding Protein Prediction Based on Deep Learning Feature Fusion 17th

DNA-Binding Protein Prediction Based on Deep Learning Featur...

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17th international conference on Intelligent computing, ICIC 2021

作者： Guan, Shixuan Jiang, Tengsheng Lu, Weizhong Fu, Qiming Li, Haiou Wu, Hongjie School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou215009 China

ISBN: (纸本)9783030845315

dna-binding protein is a special kind of protein. It can interact with dna, play an important role in various gene-related life activities, and is closely related to many diseases. therefore, it is of great significance to study the identification methods of dna-binding proteins. However, traditional biological experiment methods require a lot of human resources and material resources. It cannot meet the trend of rapid increase in protein sequences. In this article, a tool for dna-binding protein prediction based on Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) neural networks is proposed. It can not only extract features from the original sequence of a protein, but also extract related features from the co-evolution relationship of the protein. Compared with other methods, the experimental results of this model are more accurate. © 2021, Springer Nature Switzerland AG.

关键词： Proteins

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Solution to Motif Finding Problem in Membranes 17th

Solution to Motif Finding Problem in Membranes

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17th international conference on Membrane computing (CMC)

作者： Gapuz, Katrina B. Mendoza, Ephraim D. Juayong, Richelle Ann B. Hernandez, Nestine Hope S. Cabarle, Francis George C. Adorna, Henry N. Univ Philippines Diliman Dept Comp Sci Algorithms & Complex Lab Quezon City 1101 Philippines

ISBN: (纸本)9783319540726;9783319540719

the study of genes is an important field of biology. A way to understand genetic composition is through finding regularly occurring nucleotide sequences, or motifs, in a dna sequence. However, finding these motifs is difficult and is shown to be NP-complete. In this paper, we use a variant of P systems called Evolution-Communication P systems with Energy using string objects to solve the Motif Finding Problem in O(lt)-time where l is the length of the motif and t is the number of dna sequences given.

关键词： Membrane computing Evolution-communication P systems with energy Motif finding

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Reconfigurable Nanobook Structure Driven by Polymerase-Triggered dna Strand Displacement 1

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17th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2022

作者： Chen, Kuiting Chen, Zhekun Xie, Chun Pan, Linqiang Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

Due to its high degree of customization, dna origami provides a versatile platform with which to engineer nanoscale structures and devices. Reconfigurable nanodevices driven by dna strand displacement accomplish the task of transition between different conformations, endowing dna origami with application values. Herein, we propose a strategy to regulate the conformation of dna origami using the polymerase-triggered dna strand displacement (PTSD) reaction. We design a book-shaped dna origami structure consisting of four pages connected into a cuboid shape. the PTSD reactions initiated by different primer strands selectively remove the connecting strand, transforming the nano book into a two-page or a four-page conformation. We utilize three primer strands to remove thirty-five connecting strands and construct three conformations of the identical dna origami, illustrating that the PTSD reaction is an effective tool for the reconfiguration of dna origami. the statistical results of TEM images prove the effectiveness of the proposed method. Our work on the development of PTSD-driven reconfigurable nanostructure will offer a new way to create intelligent materials for advanced nanotechnology applications. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： dna

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5th international conference on theory and Practice of Natural computing, TPNC 2016

5th International Conference on Theory and Practice of Natur...

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5th international conference on theory and Practice of Natural computing, TPNC 2016

ISBN: (纸本)9783319490007

the proceedings contain 17 papers. the special focus in this conference is on Invited Talk, Applications of Natural computing, Evolutionary Computation, Formal Models and Machine Learning. the topics include: Managing natural noise in recommender systems;realization of periodic functions by self-stabilizing population protocols with synchronous handshakes;localized load balancing in RFID systems;how to implement a random bisection cut;a discrete artificial bee colony algorithm based on similarity for graph coloring problems;a multi-objective evolutionary approach to Pareto optimal model trees. a preliminary study;real time traffic intersection management using multi-objective evolutionary algorithm;simulating stochastic dynamic interactions with spatial information and flux;implementation of Turing machine using dna strand displacement;a quantum annealing approach to biclustering;determining player skill in the game of go with deep neural networks;flexible generalized fuzzy Petri nets for rule-based systems and learning grammar rules in probabilistic grammar-based genetic programming.

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Logic circuit design of sixteen-input encoder by dna strand displacement 1

引用

13th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2018

作者： Wang, Yanfeng Lv, Aolong Huang, Chun Sun, Junwei Henan Key Lab of Information-Based Electrical Appliances Zhengzhou University of Light Industry Zhengzhou450002 China School of Electrical Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

ISBN: (数字)9789811328299

ISBN: (纸本)9789811328282

As a very powerful tool, dna strand displacement technology is widely used in molecular calculations, which has received more and more attention from people. It has achieved rapid development in recent years. In this paper, a sixteen-input encoder based on dna strand displacement is designed, including dual-rail circuits and seesaw circuits based on dna strand displacement. Visual DSD is a visualization software with compiling and emulation capabilities. All reactions of encoding and simulation are performed in the visualization software Visual DSD. By changing the input signal, the accurate output can be obtained, the function of sixteen-input encoder in digital circuit is realized. With Visual DSD software, more complex logic operations are implemented based on dna strand displacement. this kind of research based on dual-rail circuits by dna strand displacement have great prospects for the development and practical application of biological information processing and molecular computing. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Visualization

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Complex logic circuit of three-input and nine-output by dna strand displacement 13th

Complex logic circuit of three-input and nine-output by DNA ...

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13th international conference on Bio-Inspired computing: theories and Applications, BIC-TA 2018

作者： Wang, Yanfeng Yuan, Guodong Huang, Chun Sun, Junwei Henan Key Lab of Information-Based Electrical Appliances Zhengzhou University of Light Industry Zhengzhou450002 China School of Electrical and Information Engineering Zhengzhou University of Light Industry Zhengzhou450002 China

ISBN: (纸本)9789811328282

In recent years, dna strand displacement technology has developed rapidly with the advantages of high-performance parallel computing and large information capacity. dna strand displacement technology is a dynamic dna nanotechnology developed on the basis of dna self-assembly technology. dna strand displacement technology can realize dynamic connection between input signal and output signal, and it is a method for constructing logic gates and logic circuits. According to the basic principle of dna strand displacement, this paper studies the specific function of the molecular logic circuit model, and constructs a logic circuit with three input and nine output. then a biochemical logic circuit is built based on the dual-rail thought and the construction of seesaw gate. Finally, dna strand displacement simulation platform Visual DSD is used to verify the rationality of the model. It lays the foundation for constructing complex logic circuits. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Timing circuits

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