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Combining greedy method and genetic algorithm to identify transcription factor binding sites

Combining greedy method and genetic algorithm to identify tr...

引用

6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence, HIS-NCEI 2006

作者： Wanyu, Wang Xiaoyu, Chang Chunguang, Zhou Key Laboratory of Symbol Computation and Knowledge Engineering Juin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769526624

Identification of Transcription Factor Binding Sites (TFBS) from the upstream region of genes remains a highly important and unsolved problem particularly in higher eukaryotic genomes. In this paper, we propose a novel approach to identify transcription factor binding sites. This approach combines greedy method and genetic algorithm (CGGA) to search conserved segment in the given sequence set. A new greedy method which can efficiently search a local optimal result is proposed. In order to solve the high complexity of this algorithm, we also give an effective improvement for this method. Then, we describe how to combine genetic algorithm with this greedy method to find the more optimal results. Greedy method is combined to the fitness function of the genetic algorithm. We apply this approach on two different TFBS sets and the results show that it can find correct result both effective and efficient, and for CRP binding sites, it get a more accurate result than Gibbs Sampler, AlignACE and MDGA. © 2006 IEEE.

关键词： Transcription factors

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An adaptive stochastic collision detection between deformable objects using particle swarm optimization

An adaptive stochastic collision detection between deformabl...

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EvoWorkshops 2006: EvoBIO, EvoCOMNET, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, and EvoSTOC

作者： Tianzhu, Wang Wenhui, Li Yi, Wang Zihou, Ge Dongfeng, Han Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)3540332375

In this paper, we present an efficient method for detecting collisions between highly deformable objects, which is a combination of newly developed stochastic method and Particle Swarm Optimization (PSO) algorithm. Firstly, our algorithm samples primitive pairs within the models to construct a discrete binary search space for PSO, and in this way user can balance performance and detection quality. Besides a particle update process is added in every time step to handle the dynamic environments caused by deformations. Our algorithm is also very general that makes no assumptions about the input models and doesn't need to store additional data structures either. In the end, we give the precision and efficiency evaluation about the algorithm and find it might be a reasonable choice for complex deformable models in collision detection systems. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Intelligent agents

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An ontology-based method in information translation

An ontology-based method in information translation

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2nd International Conference on Semantics, knowledge, and Grid, SKG 2006

作者： Bai, Yan Liu, Dayou Open Symbol Computation and Knowledge Engineering Laboratory of State Education Ministry College of Computer Science and Technology Jilin University China

ISBN: (纸本)076952673X

An ontology-based method named AOBM is proposed in this paper. It fully takes into account the factors that will afect the communication, and using ontology can be represented in agent's knowledge base. Pmvided ontology did not belong to the public data or have any public ontology, AOBM establishes a layering algorithm, which is able to avoid logical exception handling policies, ensure the right understanding of the communication entity concept, and resolve the consistency problem of the concept translation. Experimental results show that AOBM is superior to other methods, and can effectively improve the communication consistency of a mobile agent system under certain conditions. © 2006 IEEE.

关键词： Ontology

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Modeling and refining directional relations based on fuzzy mathematical morphology

Modeling and refining directional relations based on fuzzy m...

引用

High-Power Diode Laser Technology and Applications IV

作者： Sun, Haibin Li, Wenhui Key Laboratory of Symbol Computation Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)0819461466

In this paper, we investigate the deficiency of Goyal and Egenhofer's method for modeling cardinal directional relations between simple regions and provide the computational model based on the concept of mathematical morphology, which can be a complement and refinement of Goyal and Egenhofer's model for crisp regions. Based on fuzzy set theory, we extend Goyal and Egenhofer's model to handle fuzziness and provide a computational model based on alpha-morphology, which combines fuzzy set theory and mathematical morphology, to refine the fuzzy cardinal directional relations. Then the computational problems are investigated. We also give an example of spatial configuration in 2-dimensional discrete space. The experiment results confirm the cognitive plausibility of our computational models. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Fuzzy sets

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Identification of transcription factor binding sites using GA and PSO

Identification of transcription factor binding sites using G...

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6th International Conference on Intelligent Systems Design and Applications (ISDA 2006)

作者： Chang, Xiao-Yu Zhou, Chun-Guang Li, Yan-Wen Hu, Ping Key Laboratory of Symbol Computation and J Knowledge Engineering Jilin University Ministry of Education China Department of Computer Science Northeast Normal University Changchun 130012 China

ISBN: (纸本)0769525288

Identification of transcription factor binding sites from the upstream regions of genes is a highly important and unsolved problem. In this paper, we propose a novel framework for using evolutionary algorithm to solve this challenging issue. Under this framework, we use two prevalent evolutionary algorithms: Genetic, Algorithm (GA) and Particle Swarm Optimization (PSO) to find unknown sites in a collection of relatively long intergenic sequences that are suspected of being bound by the same factor. This paper represents binding sites motif to position weight matrix (PWM) and introduces how to code PWM to genome for GA and how to code it to particle for PSO. We apply these two algorithms to 5 different yeast Saccharomyces Cerevisiae transcription factor binding sites and CRP binding sites. The results on Saccharomyces Cerevisiae show that it can find the correct binding sites motifs, and the result on CRP shows that these two algorithms can achieve more accuracy than MEME and Gibbs Sampler.

关键词： Binding sites

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An efficient method for very large scale out-of-core terrain visualization

An efficient method for very large scale out-of-core terrain...

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16th International Conference on Artificial Reality and Telexistence - Workshops, ICAT 2006

作者： Zhang, Huijie Sun, Jigui Yu, Haihong Qi, Changsong College of Computer Science and Technology Jilin University College of Computer Science Northeast Normal University Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education

ISBN: (纸本)076952754X

Large scale terrain visualization with high-resolution has an increasing demand in many research fields. To realize the efficient rendering of terrain, this paper presents an out-of-core terrain visualization method based on multi-resolution storage techniques. In external memory, the terrain data set is subdivided from top to bottom to build a multi-resolution hierarchical structure based on a quad-tree. The hierarchical structure can decimate the elevation data that must be loaded into internal memory. Thus it can improve the efficiency of I/O access greatly. Moreover, in order to implement rapid data retrieval of the real time terrain flyover, an efficient indexing algorithm is proposed, in which those nodes in the hierarchical structure will be divided into several clusters in terms of the similarities of static error and the closed space constraint. In addition, a method for crack-free is also proposed here. The comprehensive experiment conducted on the GTOP30 data set shows that this approach outperforms the Block and the Hierarchy algorithms in the both ways of efficiency and simplification ratio. © 2006 IEEE.

关键词： Efficiency

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A spectrum-based support vector algorithm for relational data semi-supervised classification

引用

13th International Conference on Neural Information Processing, ICONIP 2006

作者： Ping, Ling Zhe, Wang Chunguang, Zhou Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China School of Computer Science Xuzhou Normal University Xuzhou 221116 China

ISBN: (纸本)3540464794

A Spectrum-based Support Vector Algorithm (SSVA) to resolve semi-supervised classification for relational data is presented in this paper. SSVA extracts data representatives and groups them with spectral analysis. Label assignment is done according to affinities between data and data representatives. The Kernel function encoded in SSVA is defined to rear to relational version and parameterized by supervisory information. Another point is the selftuning of penalty coefficient and Kernel scale parameter to eliminate the need of searching parameter spaces. Experiments on real datasets demonstrate the performance and efficiency of SSVA. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Learning algorithms

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Adaptive support vector clustering for multi-relational data mining

Adaptive support vector clustering for multi-relational data...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Ling, Ping Zhou, Chun-Guang Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China School of Computer Science Xuzhou Normal University Xuzhou 221116 China

ISBN: (纸本)354034439X

A novel self Adaptive Support Vector Clustering algorithm (ASVC) is proposed in this paper to cluster dataset with diverse dispersions. And a Kernel function is defined to measure affinity between multi-relational data. Task of clustering multi-relational data is addressed by integrating the designed Kernel into ASVC. Experimental results indicate that the designed Kernel can capture structured features well and ASVC is of fine performance. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Data mining

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Fuzzy neural network optimization by a particle swarm optimization algorithm

Fuzzy neural network optimization by a particle swarm optimi...

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3rd International Symposium on Neural Networks, ISNN 2006 - Advances in Neural Networks

作者： Ma, Ming Zhang, Li-Biao Ma, Jie Zhou, Chun-Guang Key Laboratory for Symbol Computation and Knowledge Engineering Jilin University National Education Ministry of China Changchun 130012 China Information Manage Center Beihua University Jilin 132013 China

ISBN: (纸本)354034439X

Designing a set of fuzzy neural networks can be considered as solving a multi-objective optimization problem. An algorithm for solving the multi-objective optimization problem is presented based on particle swarm optimization through the improvement of the selection manner for global and individual extremum. The search for the Pareto Optimal Set of fuzzy neural networks optimization problems is performed, Numerical simulations for taste identification of tea show the effectiveness of the proposed algorithm. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Neural networks

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Fast kernel for calculating structural information similarities

Fast kernel for calculating structural information similarit...

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3rd IEEE International Conference on Intelligent Systems

作者： Wei, Jin-Mao Wang, Shu-Qin Wang, Jing You, Jun-Ping Institute of Computational Intelligence Northeast Normal University Open Symbol Computation and Knowledge Engineering Laboratory of State Education Jilin University Changchun Jilin 130024 China School of Mathematics and Statistics Northeast Normal University Changchun Jilin 130024 China

ISBN: (纸本)9781424401956

Structural similarity computation plays a crucial role in many applications such as in searching similar documents, in comparing chemical compounds, in finding genetic similarities, etc. We propose in this paper to use structural information content (SIC) for measuring structural information, considering both the nodes and edges of trees. We utilize a binary encoding approach for assigning the weights of different layer nodes and determining if some tree is a subtree of another tree. By defining a fast kernel and recursively computing SICs, we evaluate the structural information similarities of data trees to pattern trees. In the paper, we present the algorithm for calculating SICs with computation complexity of O(n), and use simple examples to instantiate the performance of the proposed method..

关键词： structural information content structural similarity structural pattern analysis web mining

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