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Identification of a combination of SNPs associated with Graves' disease using swarm intelligence

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Science China(Life Sciences) 2011年第2期54卷 139-145页

作者： WEI Bin peng qinke ZHANG QuanWei LI ChenYao State Key Laboratory for Manufacturing Systems Engineering and School of Electronic and Information Engineering Xi’an Jiaotong UniversityXi’an 710049China MOE Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong UniversityXi’an 710049China Electronic and Information School of Xi’an Jiaotong University Xi’an 710049China

Graves' disease,the production of thyroid-stimulating hormone receptor-stimulating antibodies leading to hyperthyroidism,is one of the most common forms of human autoimmune *** is widely agreed that complex diseases are not controlled simply by an individual gene or DNA variation but by their *** nucleotide polymorphisms(SNPs),which are the most common form of DNA variation,have great potential as a medical diagnostic *** this paper,the P-value is used as a SNP pre-selection criterion,and a wrapper algorithm with binary particle swarm optimization is used to find the rule for discriminating between affected and control *** analyzed the association between combinations of SNPs and Graves' disease by investigating 108 SNPs in 384 cases and 652 *** evaluated our method by differentiating between cases and controls in a five-fold cross validation test,and it achieved a 72.9% prediction accuracy with a combination of 17 *** experimental results showed that SNPs,even those with a high P-value,have a greater effect on Graves' disease when acting in a combination.

关键词： Graves' disease single nucleotide polymorphism case-control study swarm intelligence

Bayesian optimization algorithm-based methods searching for risk/protective factors

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Chinese Science Bulletin 2013年第23期58卷 2828-2835页

作者： WEI Bin peng qinke CHEN Xiao ZHAO Jing Engineering University of CAPF Electronic and Information School Xi'an Jiaotong University Key Laboratory for Intelligent Networks and Network Security of Ministry of Education Xi'an Jiaotong University State Key Laboratory for Manufacturing Systems Engineering and School of Electronic and Information Engineering Xi'an Jiaotong University

The risks of developing complex diseases are likely to be determined by single nucleotide polymorphisms (SNPs), which are the most common form of DNA variations. Rapidly developing genotyping technologies have made it possible to assess the influence of SNPs on a particular disease. The aim of this paper is to identify the risk/protective factors of a disease, which are modeled as a subset of SNPs (with specified alleles) with the maximum odds ratio. On the basis of risk/protective factor and the relationship between nucleotides and amino acids, two novel risk/protective factors (called k-relaxed risk/protective factors and weighted-relaxed risk/protective factors) are proposed to consider more complex disease-associated SNPs. However, the enormous amount of possible SNPs interactions presents a mathematical and computational challenge. In this paper, we use the Bayesian Optimization Algorithm (BOA) to search for the risk/protective factors of a particular disease. Determining the Bayesian network (BN) structure is NP-hard; therefore, the binary particle swarm optimization was used to determine the BN structure. The proposed algorithm was tested on four datasets. Experimental results showed that the algorithm proposed in this paper is a promising method for discovering SNPs interactions that cause/prevent diseases.

关键词：贝叶斯算法保护因子风险单核苷酸多态性基础贝叶斯优化算法 NP-hard 粒子群优化算法

Suboptimal distributed Kalman filtering fusion with feedback

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Journal of Systems Engineering and Electronics 2005年第4期16卷 746-749页

作者： Zhao Minhua Zhu Zhuanmin Shi Meng peng qinke Huang Yongxuan School of Economics & Finance Xi'an Jiaotong Univ. Xi'an 710049 P. R. China School of Sdenee Xi'an Jiaotong Univ. Xi'an 710049 P. R. China School of Electronics and information Engineering Xi'an Jiaotong Univ. Xi'an 710049 P. R. China

In order to improve the accuracy of fusion algorithm, feedback is introduced into Kalman filtering fusion. Fusion center broadcasts its latest estimated states to the local sensors, which can improve the performance of local tracking error through reducing the oovariance of each local error, and only needs calculating the trace of error variance matrices without calculating the inverse of error variance matrices. Simulation results show that it can reduce the ecmputational complexity and the oovariance of error, and it is oonvenient for engineering applications.

关键词： feedback Kalman filtering data fusion.

DNA splice site sequences clustering method for conservativeness analysis

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Progress in Natural Science:Materials International 2009年第4期19卷 511-516页

作者： Quanwei Zhang, qinke peng, Tao Xu State Key Laboratory for Manufacturing Systems Engineering, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China State Key Laboratory for Manufacturing Systems Engineering School of Electronic and Information Engineering Xi’an Jiaotong University Xi’an 710049 China

DNA sequences that are near to splice sites have remarkable conservativeness, and many researchers have contributed to the prediction of splice site. In order to mine the underlying biological knowledge, we analyze the conservativeness of DNA splice site adjacent sequences by clustering. Firstly, we propose a kind of DNA splice site sequences clustering method which is based on DBSCAN, and use four kinds of dissimilarity calculating methods. Then, we analyze the conservative feature of the clustering results and the experimental data set.

关键词： Bioinformatics processing Clustering DBSCAN Splice site

Identification of Deleterious Single Amino Acid Polymorphism Using Sequence Information Based on Feature Selection and Parameter Optimization

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Engineering（科研） 2013年第10期5卷 472-476页

作者： Xiao Chen qinke peng Jia Lv Systems Engineering Institute of Electronic and Information Engineering School Xi’an Jiaotong University Xi’an China

Most of the human genetic variations are single nucleotide polymorphisms (SNPs), and among them, non-synonymous SNPs, also known as SAPs, attract extensive interest. SAPs can be neural or disease associated. Many studies have been done to distinguish deleterious SAPs from neutral ones. Since many previous studies were based on both structural and sequence features of the SAP, these methods are not applicable when protein structures are not available. In the current paper, we developed a method based on UMDA and SVM using protein sequence information to predict SAP’s disease association. We extracted a set of features that are independent of protein structure for each SAP. Then a SVM-based machine-learning classifier that used grid search to tune parameters was applied to predict the possible disease associa-tion of SAPs. The SVM method reaches good prediction accuracy. Since the input data of SVM contain irrelevant and noisy features and parameters of SVM also affect the prediction performance, we introduced UMDA-based wrapper approach to search for the ‘best’ solution. The UMDA-based method greatly improved prediction performance. Com-pared with current method, our method achieved better performance.

关键词： Single Amino Acid Polymorphisms Support Vector Machine Univariate Marginal Distribution Algorithm

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一种集群服务器并行网页预取模型

计算机工程 2005年第24期31卷 47-49页

作者：燕彩蓉沈钧毅彭勤科西安交通大学软件所西安交通大学系统工程所西安710049

提出了集群服务器并行网页预取模型,模型采用了马尔科夫链分析访问路径并在Web集群服务器的各节点上并行预取页面,把集群技术的高性能和高可靠性与预取技术的快速响应能力结合起来。实验表明,将此模型应用于集群服务器的分发器上,服务... 详细信息

提出了集群服务器并行网页预取模型,模型采用了马尔科夫链分析访问路径并在Web集群服务器的各节点上并行预取页面,把集群技术的高性能和高可靠性与预取技术的快速响应能力结合起来。实验表明,将此模型应用于集群服务器的分发器上,服务器系统具有更高的请求命中率和更大的吞吐量。

关键词：集群服务器并行网页预取马尔科夫链

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Hybrid:一种两阶段的聚类算法

计算机工程 2005年第13期31卷 1-3,50页

作者：周兵沈钧毅彭勤科东北大学秦皇岛分校计算机工程系秦皇岛066004 西安交通大学电子与信息工程学院西安710049

提出了一种两阶段的聚类方法:Hybrid。第一阶段产生大小相同的圆形原子聚类;第二阶段合并原子聚类形成任意形状和大小的聚合聚类。在扩展边界时,不但考虑原子聚类间的距离,还考虑原子聚类的密度相似度。这样可以更好地排除“噪音”的影... 详细信息

提出了一种两阶段的聚类方法:Hybrid。第一阶段产生大小相同的圆形原子聚类;第二阶段合并原子聚类形成任意形状和大小的聚合聚类。在扩展边界时,不但考虑原子聚类间的距离,还考虑原子聚类的密度相似度。这样可以更好地排除“噪音”的影响,得到内部结构更加趋同的聚合聚类。

关键词：数据挖掘聚类算法原子聚类聚合聚类噪音

一种基于内容分发请求的Web集群服务器研究

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西安交通大学学报 2005年第4期39卷 380-383页

作者：燕彩蓉彭勤科沈钧毅西安交通大学电子与信息工程学院西安710049

针对Web集群服务器请求内容的分布特点,提出了一种基于关联内容的请求分发(ACARD)算法.该算法首先以缓存大小为限制,采用FP tree方法挖掘用户的Web使用模式,并把它们所对应的文档映射到不同的后端服务器,然后由前端服务器根据请求的内... 详细信息

针对Web集群服务器请求内容的分布特点,提出了一种基于关联内容的请求分发(ACARD)算法.该算法首先以缓存大小为限制,采用FP tree方法挖掘用户的Web使用模式,并把它们所对应的文档映射到不同的后端服务器,然后由前端服务器根据请求的内容匹配相应的模式并进行转发.这种文档的自适应分布提高了集群系统的磁盘利用率和缓存命中率.实验表明,基于内核态的请求分发算法的性能远优于基于用户态的算法,而且在内核态下,ACARD相对加权最小连接算法的系统平均吞吐量可提高20 4%.

关键词： Web集群服务器基于内容分发请求自适应缓存命中率

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混合因子矩阵分解推荐算法

西安交通大学学报 2016年第12期50卷 87-91页

作者：赵长伟彭勤科张志勇西安交通大学电子与信息工程学院西安710049 河南科技大学信息工程学院河南洛阳471023

针对矩阵分解推荐算法在潜在属性与已知属性之间不能建立对应关系的问题,提出了一种混合显式属性与隐式属性的矩阵分解算法。该算法使用显式属性的相关性对因子矩阵进行约束,能够抑制稀疏数据矩阵分解中过拟合的问题,提高推荐精度,由于... 详细信息

针对矩阵分解推荐算法在潜在属性与已知属性之间不能建立对应关系的问题,提出了一种混合显式属性与隐式属性的矩阵分解算法。该算法使用显式属性的相关性对因子矩阵进行约束,能够抑制稀疏数据矩阵分解中过拟合的问题,提高推荐精度,由于因子矩阵中包含显式属性,所以混合因子矩阵分解算法可以实现对新用户和新产品推荐,部分地解决了冷启动问题,实现了从评分数据到显式属性的映射,并对推荐结果给出一定的解释。在MovieLens数据集上的实验结果表明:相同因子数下,混合因子矩阵分解算法的推荐精度均优于偏置概率矩阵分解算法,并能够基于显式属性实现对新产品的推荐。

关键词：推荐算法矩阵分解混合因子推荐解释冷启动