检索结果-内蒙古大学图书馆

Bayesian inference for epistasis association mapping in case-control studies

ICIC Express Letters 2015年第1期9卷 261-268页

作者： Zhou, Zhihui Liu, Guixia Su, Lingtao Tian, Yuan College of Computer Science and Technology Jilin University No. 2699 Qianjin Avenue Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University No. 2699 Qianjin Avenue Changchun China

A genome-wide association study (GWAS) typically involves detecting epistatic interactions of multiple genetic variants on the susceptibility of complex human diseases. As the most abundant source of genetic variation in human genome, the number of single nucleotide polymorphisms (SNPs) reaches millions in public datasets and SNP data collected from thousands of individuals in case-control studies may shed light on our understanding of epistatic interactions. Various methods have been proposed in previous literature for identifying genetic interactions, but they are infeasible for GWAS as biology data is too large, we here propose a method ‘epistasis group based on Bayesian inference’ (EGBI). EGBI applies a Bayesian marker partition model to investigate observed case-control data and computes the posterior distribution of each epistasis group that is associated with the disease via Markov chain Monte Carlo (MCMC). When applied to both simulated data and WTCCC type 1 diabetes data, EGBI successfully identified many known susceptible genes including CTLA4 and MHC and performed more powerfully than its competitors.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

A DE algorithm combined with lévy flight for reliability redundancy allocation problems

引用

International Journal of Hybrid Information Technology 2015年第5期8卷 113-118页

作者： Liu, Yubao Qin, Guihe College of Computer Science and Technology Jilin University Changchun China College of Computer Science and Technology Changchun University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China

In this paper, a differential evolution (DE) algorithm combined with Lévy flight is proposed to solve the reliability redundancy allocation problems. The Lévy flight is incorporated to enhance the ability of global search of differential evolution algorithm. DE is used for local search mainly. The method considers the trade-off of the diversification and the intensification simultaneously. Experimental results for three benchmark problems demonstrate that the proposed algorithm is more effective for solving the reliability redundancy allocation problems. © 2015 SERSC.

关键词： Nonlinear programming

来源：评论

学校读者我要写书评

暂无评论

Experience Replay for Least-Squares Policy Iteration

引用

IEEE/CAA Journal of Automatica Sinica 2014年第3期1卷 274-281页

作者： Quan Liu Xin Zhou Fei Zhu Qiming Fu Yuchen Fu the School of Computer Science and Technology Soochow University the Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University the School of Computer Science and Technology Soochow University

Policy iteration,which evaluates and improves the control policy iteratively,is a reinforcement learning *** evaluation with the least-squares method can draw more useful information from the empirical data and therefore improve the data ***,most existing online least-squares policy iteration methods only use each sample just once,resulting in the low utilization *** the goal of improving the utilization efficiency,we propose an experience replay for least-squares policy iteration(ERLSPI)and prove its *** method combines online least-squares policy iteration method with experience replay,stores the samples which are generated online,and reuses these samples with least-squares method to update the control *** apply the ERLSPI method for the inverted pendulum system,a typical benchmark *** experimental results show that the method can effectively take advantage of the previous experience and knowledge,improve the empirical utilization efficiency,and accelerate the convergence speed.

关键词： Learning (artificial intelligence) Markov processes computational efficiency Convergence Least squares methods

来源：评论

学校读者我要写书评

暂无评论

Methods for gene selection in microarrays based on data clustering on local SVM-RFE

引用

Journal of computational Information Systems 2015年第16期11卷 5825-5832页

作者： Cao, Zhongbo Du, Wei Sun, Ying Liang, Yanchun Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China Department of Computer Science and Technology Zhuhai College of Jilin University Zhuhai China School of Management Science and Information Engineering Jilin University of Finance and Economics Changchun China

Most of the microarray expression data have tens of thousands of genes but very small number of samples. Feature selection has been widely used to extract the subset of informative genes. Though many feature selection methods have been proposed, the Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithm is one of the best for microarray expression data analysis. However, SVM-RFE is not a stable and robust algorithm in some cases. The purpose of this article is to design a novel gene selection method for microarray expression data analysis, which is more effective, flexible and robust than normal SVM-RFE. In this article, the Local SVM-RFE (L-SR), Cluster SVM-RFE (C-SR) and Cluster Local SVM-RFE (CL-SR) methods for feature selection are proposed which eliminate irrelevant genes effectively and automatically. Experimental results obtained by using six cancer related datasets on different classifiers demonstrate that the proposed methods in this article are superior to normal SVM-RFE. Moreover, compared with the mRMR, GA-KNN and SVM-RCE, the proposed algorithm shows better performance in best and average accuracies comparison. © 2015 by Binary Information Press

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Painlevé Property and Integrability of Polynomial Dynamical Systems

引用

Communications in Mathematical Research 2014年第4期30卷 358-368页

作者： Li Wen-lei Shi Shao-yun School of Mathematics Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University

The main purpose of this paper is to investigate the connection between the Painlev′e property and the integrability of polynomial dynamical systems. We show that if a polynomial dynamical system has Painlev′e property, then it admits certain class of first integrals. We also present some relationships between the Painlev′e property and the structure of the differential Galois group of the corresponding variational equations along some complex integral curve.

关键词： Painlev′e property integrability differential Galois group

来源：评论

学校读者我要写书评

暂无评论

Modulating a Local Shape Descriptor through Biologically Inspired Color Feature

引用

Journal of Bionic engineering 2014年第2期11卷 311-321页

作者： Hongwei Zhao Baoyu Zhou Pingping Liu Tianjiao Zhao School of Computer Science and Technology Jilin University Changchun 130012 P. R. China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 P. R. China

This paper presents a biologically inspired local image descriptor that combines color and shape features. Compared with previous descriptors, red-cyan cells associated with L, M, and S cones （L for long, M for medium, and S for short） are used to indicate one of the opponent color channels. Stepping forward from state-of-the-art color feature extraction, we exploit a new approach to compute the color orientation and magnitudes of three opponent color channels, namely, red-green, blue-yellow, and red-cyan, in two-dimensional space. Color orientation is calculated in histograms with magnitude weighting. We linearly concatenate the four-color-opponent-channel histogram and scale-invariant-feamre-transform histogram in the final step. We apply our biologically inspired descriptor to describe the local image feature. Quantitative comparisons with state-of-the-art descriptors demonstrate the significant advantages of maintaining invariance to photometric and geometric changes in image matching, particularly in cases, such as illumination variation and image blurring, where more color contrast information is observed.

关键词： local image descriptor color opponent color scale-invariant feature transform image matching

来源：评论

学校读者我要写书评

暂无评论

A new epistasis detecting algorithm based on ant colony optimization 14

A new epistasis detecting algorithm based on ant colony opti...

引用

6th International Conference on Internet Multimedia Computing and Service, ICIMCS 2014

作者： Zhou, Zhihui Liu, Guixia Su, Lingtao Han, Liang Yan, Lun College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9781450328104

The rapid developments of chip-based technology have greatly improved human genetics and made routine the access of thousands of single nucleotide polymorphisms (SNPs) contributing to an informatics challenge. The characterization and interpretation of genes and gene-gene interactions that affect the susceptibility of common, complex multifactorial diseases is a computational and statistical challenge in genome-wide association studies (GWAS). Various methods have been proposed, but they have dificulty to be directly applied to GWAS caused by excessive search space and intensive computational burden. In this paper, we propose an ant colony optimization (ACO) based algorithm by combining the pheromone updating rule with the heuristic information. We tested power performance of our algorithm by conducting suficient experiments including a wide range of simulated datasets experiments and a real genome-wide dataset experiment. Experimental results demonstrate that our algorithm is time efficient and gain good performance in the term of the power of prediction accuracy. Copyright 2014 ACM.

关键词： Ant colony optimization

来源：评论

学校读者我要写书评

暂无评论

Density and sliding window-based clustering over evolving data streams

引用

ICIC Express Letters, Part B: Applications 2015年第8期6卷 2275-2283页

作者： Yu, Yanwei Zhao, Jindong Zhang, Yonggang Wen, Changci School of Computer and Control Engineering Yantai University No. 32 Qingquan Road Laishan District Yantai China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University No. 2699 Qianjin Street Changchun China Jingchang Office of Chinese Airforce No. 11 Shuangyuan Road Shijingshan District Beijing China

Density-based clustering over huge volumes of evolving data streams is critical for many modern applications ranging from network traffic monitoring to moving object management. In this work, we propose an efficient density-based clustering algorithm under sliding window environments to handle evolving data streams. First, we use cell partition optimization to fast determine points’ status instead of expensive completed neighbor query for core points. Second, we cluster new and expired points with cell-cluster structure. Cell-cluster leverages relationships of connected cells around points to complete classification of the points in the cells. Under the effect analysis of new and expired points, we then design an exact clustering framework with cell partition and cell-cluster in streaming windows. Our experimental evaluation, using both real and synthetic streaming data, demonstrates that our algorithm shows effectiveness in capturing the clusters with noise and performs faster than state-of-the art methods, and scales to high volume data streams. © 2015, ICIC International.

关键词： Cells

来源：评论

学校读者我要写书评

暂无评论

Detecting epistasis by LASSO-penalized-model search algorithm in human Genome-Wide Association Studies

Detecting epistasis by LASSO-penalized-model search algorith...

引用

4th International Conference on Materials Science and Information Technology, MSIT 2014

作者： Zhou, Zhi Hui Liu, Gui Xia Su, Ling Tao Han, Liang Yan, Lun College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783038351733

Extensive studies have shown that many complex diseases are influenced by interaction of certain genes, while due to the limitations and drawbacks of adopting logistic regression (LR) to detect epistasis in human Genome-Wide Association Studies (GWAS), we propose a new method named LASSO-penalized-model search algorithm (LPMA) by restricting it to a tuning constant and combining it with a penalization of the L1-norm of the complexity parameter, and it is implemented utilizing the idea of multi-step strategy. LASSO penalized regression particularly shows advantageous properties when the number of factors far exceeds the number of samples. We compare the performance of LPMA with its competitors. Through simulated data experiments, LPMA performs better regarding to the identification of epistasis and prediction accuracy. © (2014) Trans Tech Publications, Switzerland.

关键词： Genes

来源：评论

学校读者我要写书评

暂无评论

Comparative Study on Metaheuristic-Based Feature Selection for Cotton Foreign Fibers Recognition

Comparative Study on Metaheuristic-Based Feature Selection f...

引用

The 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Xuehua Zhao Xueyan Liu Daoliang Li Huiling Chen Shuangyin Liu Xinbin Yang Shaobin Zhan Wenyong Zhao School of Digital Media Shenzhen Institute of Information Technology Key Laboratory of Symbolic Computation and Knowledge Engineer (Jilin University) Ministry of Education College of Information and Electrical Engineering China Agricultural University College of Physics and Electronic Information Wenzhou University College of Information Guangdong Ocean University

ISBN: (纸本)9783319483566

The excellent feature set or feature combination of cotton foreign fibers is great significant to improve the performance of machine-vision-based recognition system of cotton foreign fibers. To find the excellent feature sets offoreign fibers, in this paper presents three metaheuristic-based feature selection approaches for cotton foreign fibers recognition, which are particle swarm optimization, ant colony optimization and genetic algorithm, respectively. The k-nearest neighbor classifier and support vector machine classifier with k-fold cross validation are used to evaluate the quality offeature subset and identify the cotton foreign fibers. The results show that the metaheuristic-based feature selection methods can efficiently find the optimal feature sets consisting of a few features. It is highly significant to improve the performance of recognition system for cotton foreign fibers.

关键词： Metaheuristic Feature selection Foreign fibers Recognition system Feature extraction recognition system Fiber Fibrous materials Cotton Support Vector Network

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：