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A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy

Journal of Bionic engineering 2008年第3期5卷 215-223页

作者： Shu-xue Zou Yan-xin Huang Yan Wang Chun-guang Zhou Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun 130012 P. R. China

Detecting the boundaries of protein domains is an important and challenging task in both experimental and computational structural biology. In this paper, a promising method for detecting the domain structure of a protein from sequence information alone is presented. The method is based on analyzing multiple sequence alignments derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence. Then they are combined into a single predictor using support vector machine. What is more important, the domain detection is first taken as an imbal- anced data learning problem. A novel undersampling method is proposed on distance-based maximal entropy in the feature space of Support Vector Machine （SVM）. The overall precision is about 80%. Simulation results demonstrate that the method can help not only in predicting the complete 3D structure of a protein but also in the machine learning system on general im- balanced datasets.

关键词： protein domain boundary SVM imbalanced data learning distance-based maximal entropy

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Canonical Huffman code based full-text index

引用

Progress in Natural Science:Materials International 2008年第3期18卷 325-330页

作者： Yi Zhang a,b, Zhili Pei a, Jinhui Yanga, Yanchun Liang a, a College of Computer Science and Technology, Jilin University, key laboratory of symbol computation and knowledge engineering of the Ministry of Education, Changchun 130012, China b Department of Computer Science, Jilin Technology and Business College, Changchun 130062, China College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China Department of Computer Science Jilin Technology and Business College Changchun 130062 China

Full-text indices are data structures that can be used to find any substring of a given string. Many full-text indices require space larger than the original string. In this paper, we introduce the canonical Huffman code to the wavelet tree of a string T[1. . .n]. Compared with Huffman code based wavelet tree, the memory space used to represent the shape of wavelet tree is not needed. In case of large alphabet, this part of memory is not negligible. The operations of wavelet tree are also simpler and more efficient due to the canonical Huffman code. Based on the resulting structure, the multi-key rank and select functions can be performed using at most nH0 + jRj(lglgn + lgn lgjRj)+O(nH0) bits and in O(H0) time for average cases, where H0 is the zeroth order empirical entropy of T. In the end, we present an efficient construction algorithm for this index, which is on-line and linear.

关键词： Full-text index Su?x automaton Canonical Hu?man code

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PSO based partitional clustering algorithm

引用

Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (engineering and Technology Edition) 2008年第6期38卷 1371-1377页

作者： Zhang, Chang-Sheng Sun, Ji-Gui Cui, Yan Yang, Feng-Qin Key Laboratory of Symbol Computation and Knowledge Engineering College of Computer Science and Technology Jilin University Changchun 130012 China

To obtain the optimal partition of a data set, a hybrid clustering algorithm, PKPSO, based on PSO is proposed. In the proposed PKPSO the PSO algorithm is effectively integrated with the K means algorithm. Among the population, selected candidate solutions are further optimized to improve the accuracy by the K-means algorithm. By analyzing the algorithm, the criterions for control parameters selection are determined. Partional clustering result by the proposed PKPSO is compared with that by PSO or by K-means algorithm, and results show that the global convergent property of PKPSO is better than that of the other algorithms. The PKPSO can not only overcome the shortcoming of local minimum trapping of the K-means, but also the solution precision and algorithm stability are better than that of the other two algorithm.

关键词： Clustering algorithms

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Corrigendum to “Catalog segmentation with double constraints in business” [Pattern Recognition Letters 30 (4) (2009) 440–448]

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Pattern Recognition Letters 2009年第15期30卷 1440-1440页

作者： Xiujuan Xu Yu Liu Zhe Wang Chunguang Zhou Yanchun Liang College of Computer Science Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 China School of Software Dalian University of Technology Dalian Economic and Technological Development Zone Liaoning Number 8 Road Dalian 116620 China

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Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

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Journal of Bionic engineering 2008年第2期5卷 111-119页

作者： Jin-hui Yang Liang Sun Heow Pueh Lee Yun Qian Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 P. R. China Institute of High Performance Computing Singapore 117528 Singapore Department of Mechanical Engineering National University of Singapore Singapore 117576 Singapore Institute of Electric and Information Engineering Beihua University Jilin 13202 l P. R. China

A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki＇s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.

关键词： job shop scheduling problem clonal selection algorithm simulated annealing global search local search

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The Application of Support Vector Machine to Operon Prediction

The Application of Support Vector Machine to Operon Predicti...

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International Conference on Future Generation Communication and Networking (FGCN)

作者： Xiumei Wang Wei Du Yan Wang Chen Zhang Chunguang Zhou Shuqin Wang Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China

ISBN: (纸本)9781424440085

In this paper, we apply the least-square support vector machine (LS-SVM) to operon prediction of Escherichia coli (***), with different combinations of intergenic distance, gene expression data, and phylogenetic profile. Experimental results demonstrate that the WO pairs tend to have shorter intergenic distances, higher correlation coefficient and much stronger relation of co-envoled between phylogenetic profiles. Also, we dealt with the data sets extracted from WOs¿ and TUBs¿, processed the intergenic distances with log-energy entropy, de-noised the Pearson correlation coefficients of two genes expression data with wavelet transform, and computed the Hamming distances of two phylogenetic profiles. Then we trained LS-SVM using part of the data sets and tested the trained classifier model using the rest data sets. It shows that different combinations of features could affect the prediction results. When the combination of intergenic distance, gene expression data and phylogenetic profile is taken as the input of LS-SVM in the linear kernel type, good results can be obtained, of which the accuracy, sensitivity and specificity are 92.34%, 93.54%, and 90.73%, respectively.

关键词： Support vector machines Phylogeny Gene expression Data mining Entropy Genetic expression Wavelet transforms Testing Kernel Sensitivity and specificity

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Copyright Protection Using A computational Watermarking Scheme

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The 9th International Conference for Young Computer Scientists(第九届国际青年计算机大会)

作者： Qi Jiang Dongfeng Han Yi Li Wenhui Li Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China

In this paper an efficient copyright protection watermarking algorithm is proposed. By embedding orthogonal vector into the wavelet-tree structure of the host image, we get the watermarked image. At the same time human vision system is considered to get perceptual results. We design an elaborate function for blind watermarking scheme. This function can dynamically determine the embedding position. The theory and experimental results show that our method successfully survives image processing operation, noise adding, the JPEG lossy compression and image cropping. Especially, the scheme is robust towards image sharpening and image enhancement.

关键词： copyright protection watermark wavelet tree

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An Ant Colony Optimization Method for Prize-collecting Traveling Salesman Problem with Time Windows

An Ant Colony Optimization Method for Prize-collecting Trave...

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International Conference on Natural computation (ICNC)

作者： Xiaohu Shi Liupu Wang You Zhou Yanchun Liang Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China

Focused on a variation of the Euclidean traveling salesman problem (TSP), namely the prize-collecting traveling salesman problem with time windows (PCTSPTW), this paper presents a novel ant colony optimization solving method. The time window constraints are considered in the computation for the probability of selection of the next city. The parameters of the algorithm are analyzed by experiments. Numerical results also show that the proposed method is effective for the PCTSPTW problem.

关键词： Ant colony optimization Traveling salesman problems Cities and towns Algorithm design and analysis Time factors Performance analysis Educational institutions Computer science Educational technology Laboratories

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Translating query for deep web using ontology

Translating query for deep web using ontology

引用

International Conference on Computer Science and Software engineering, CSSE 2008

作者： Hao, Hang Wanli, Zuo Fei, Ren Junhua, Wang College of Computer Science and Technology Jilin University Department of Information Science and Technology Changchun Taxation College Changchun 130117 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun 130012 China College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9780769533360

The E-commerce information on the Surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the web crawlers. The only way to access the backend database is through query interface. Extracting valid attributes from the query forms and automatic translating the source query into a target query is a solvable way for addressing the current limitations in accessing Deep Web data sources. To generate a valid query, we have to reconcile the key attributes and their semantic relation. We present our framework to solve the problem. To enrich the set of attributes contained in the semantic form, we use the WordNet as kinds of ontology technique and we try to find the semantic relation of the attributes in the same query from and different forms. Extensive experiments over real-word domains show the utility of our query translation framework. © 2008 IEEE.

关键词： Ontology

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An improved particle swarm optimization algorithm for flowshop scheduling problem

An improved particle swarm optimization algorithm for flowsh...

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International Conference on Information and Automation (ICIA)

作者： Bo Li Changsheng Zhang Ge Bai Erliang Zhang a. The computing center of Changchun Institute of Technology b. Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education c. Aviation university of air force Changchun China

The flowshop scheduling problem has been widely studied in the literature and many techniques have been applied to it, but few algorithms have been proposed to solve it using particle swarm optimization algorithm (PSO) based algorithm. In this paper, an improved PSO algorithm (IPSO) based on the ldquoall differentrdquo constraint is proposed to solve the flowshop scheduling problem with the objective of minimizing makespan. It combines the particle swarm optimization algorithm with genetic operators together effectively. When a particle is going to stagnates, the mutation operator is used to search its neighborhood. The proposed algorithm is tested on different scale benchmarks and compared with the recently proposed efficient algorithms. The results show that both the solution quality and the convergent speed of the IPSO algorithm precede the other two recently proposed algorithms. It can be used to solve large scale flowshop scheduling problem effectively.

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