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...
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(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.
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 b...
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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. Lab...
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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 dat...
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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 opti...
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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 on...
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.
Texture synthesis is a very active research area in computer vision and graphics, and temporal texture synthesis is one subset of it. A new temporal texture synthesis algorithm is presented, in which genetic algorithm...
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Texture synthesis is a very active research area in computer vision and graphics, and temporal texture synthesis is one subset of it. A new temporal texture synthesis algorithm is presented, in which genetic algorithm is introduced into the processes of synthesizing videos. In the algorithm, by analyzing and processing a finite source video clip, infinite video sequences that are played smoothly in vision can be obtained. Comparing with many existing temporal texture synthesis algorithms, this algorithm can get high-quality video results without complicated pre-processing of source video while it improves the efficiency of synthesis. This paper analyzes to determine the population size and the Max number of generations which influence the speed and quality of synthesis.
An efficient method for the diagnosis of breast cancer tumor is proposed based on Independent Component Analysis (ICA) and Least Square Support Vector Machine (LS-SVM). In order to save the expense of detection, first...
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A novel dynamic time delay neural network is proposed for ultrasonic motors identification and control in this paper. By introducing time delay neurons, the neural network identifier and controller of ultrasonic motor...
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An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antib...
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An improved artificial immune algorithm with a dynamic threshold is presented. The calculation for the affinity function in the real-valued coding artificial immune algorithm is modified through considering the antibody＇s fitness and setting the dynamic threshold value. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance for preventing premature convergence.
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