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Search Results: 1 - 10 of 6961 matches for " Xiaogang Gong "
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Tumor-specific gene expression patterns with gene expression profiles
Xiaogang Ruan,Yingxin Li,Jiangeng Li,Daoxiong Gong,Jinlian Wang
Science China Life Sciences , 2006, DOI: 10.1007/s11427-006-0293-1
Abstract: Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, “RFE_Relief algorithm” was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.
Application to Three-Dimensional Canonical Correlation Analysis for Feature Fusion in Image Recognition
Xiaogang Gong,Jiliu Zhou,Huilin Wu,Gang Lei
Journal of Computers , 2011, DOI: 10.4304/jcp.6.11.2427-2433
Abstract: This paper presents a three-dimensional canonical correlation analysis (TCCA) method, and applies it to feature fusion for image recognition. It is an extension of traditional canonical correlation analysis (CCA) and two-dimensional canonical correlation analysis (2DCCA). Considering two views of a three-dimensional data, the TCCA can directly find the relations between them without reshaping the data into matrices or vectors, We stress that TCCA dramatically reduce the computational complexity, compared to the CCA and 2DCCA. To evaluate the algorithm, we are using Gabor wavelet to generate the three-dimensional data, and fusing them at the feature level by TCCA. Some experiments on ORL database and JAFEE database and compared with other methods, the results show that the TCCA not only the computing complexity is lower, the recognition performance is better but also suitable for data fusion.
Research on the Improvement of Competitiveness of Chain Business Enterprises with the System Theory  [PDF]
Xiaogang Yang
Open Journal of Business and Management (OJBM) , 2016, DOI: 10.4236/ojbm.2016.43051
Abstract: Chain business enterprises face increasing competition. With the system theory, the competitiveness structure of chain business enterprises is analyzed, and practical methods and measures for the improvement of their competitiveness are provided.
The Advantages and Measures of Constructing Logistics Strategic Alliance for Chain Marketing Enterprises  [PDF]
Xiaogang Yang
American Journal of Industrial and Business Management (AJIBM) , 2016, DOI: 10.4236/ajibm.2016.67077
Abstract: The results indicated that the logistics strategic alliance has obvious advantages and benefits to economies of scale, and building strategic alliance of logistics is an effective way for the chain marketing enterprises to achieve economies of scale, which can enhance their core competitiveness. In this paper, the author pointed out the specific measures of the chain marketing enterprises to construct and consolidate logistics strategic alliance.
Education Marketing Research  [PDF]
Xiaogang Yang
Theoretical Economics Letters (TEL) , 2016, DOI: 10.4236/tel.2016.65111
Abstract: “Education marketing” is a new concept used in high frequency interiorly in recent years, but it has significantly different interpretations in the educational circles and business circles, extremely easy to cause the misuse and mix, which is not conducive to the development and application of this new subject of marketing. The analysis of this paper shows that: there are four essential differences in the understanding of “educational marketing” in the education and business circles and two suggestions are put forward to solve the problem.
Three Important Applications of Mathematics in Financial Mathematics  [PDF]
Xiaogang Yang
American Journal of Industrial and Business Management (AJIBM) , 2017, DOI: 10.4236/ajibm.2017.79077
Abstract: This paper analyzes the basic connotation of financial mathematics, financial mathematics through research development, control theory, differential game theory and capital asset pricing model from stochastic optimal, and discusses three important applications of mathematics in the financial field.
On the Emergence, Development and Prospect of Financial Mathematics  [PDF]
Xiaogang Yang
Modern Economy (ME) , 2017, DOI: 10.4236/me.2017.89078
Abstract: Since its emergence in 1980s, financial mathematics has developed into an interdisciplinary subject with independent theoretical system. On the one hand, financial mathematics has become the key technology that can be seen everywhere in finance. On the other hand, the development of Finance provides an important platform for the application of mathematics. The purpose of this paper is to analyze and summarize the emergence and development of financial mathematics, and to analyze the future of financial mathematics.
Common promoter variants of the NDUFV2 gene do not confer susceptibility to schizophrenia in Han Chinese
Wen Zhang, Xiaogang Chen, Wei Gong, Jinsong Tang, Liwen Tan, Hao Guo, Yong-Gang Yao
Behavioral and Brain Functions , 2010, DOI: 10.1186/1744-9081-6-75
Abstract: We genotyped the promoter variants of this gene (rs6506640 and rs1156044) by direct sequencing in 529 unrelated Han Chinese schizophrenia patients and 505 matched controls. Fisher's Exact test was performed to assess whether these two reported single nucleotide polymorphisms (SNPs) confer susceptibility to schizophrenia in Chinese.Allele, genotype and haplotype comparison between the case and control groups showed no statistical significance, suggesting no association between the NDUFV2 gene promoter variants and schizophrenia in Han Chinese.The role of NDUFV2 played in schizophrenia needs to be further studied. Different racial background and/or population substructure might account for the inconsistent results between studies.Mitochondrial dysfunction was considered as a risk factor for the onset of schizophrenia and other psychiatric disorders [1]. As a core component of mitochondrial respiratory chain, the 24 kD subunit of mitochondrial complex I, NADH-ubiquinone oxidoreductase flavoprotein (NDUFV2), is a hot candidate target for psychiatric disorders [2-7]. The first clue that indicated a potential positive association of the NDUFV2 gene with schizophrenia could be traced to the pioneer association and linkage study by Schwab and colleagues [8], in which they reported chromosome 18p (which contains this gene), conferred susceptibility to functional psychoses in families with schizophrenia. Subsequent analyses showed a decreased level of NDUFV2 expression in postmortem prefrontal cortex and striatum of schizophrenia patients [9-11] and in lymphoblastoid cell line of Caucasian schizophrenia patients [4], suggesting an active involvement of NDUFV2 in schizophrenia. Recent association studies further indicated that the NDUFV2 promoter haplotype, which was constituted by two SNPs (rs6506640-rs1156044), was significantly associated with schizophrenia in Japanese population [5]. This association was also found in patients with bipolar disorder from different populatio
Tumor-specific gene expression patterns with gene expression profiles
Xiaogang Ruan,Yingxin Li,Jiangeng Li,Daoxiong Gong,Jinlian Wang,

中国科学C辑(英文版) , 2006,
Abstract: Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.
A Derivative-Free Optimization Algorithm Using Sparse Grid Integration  [PDF]
Shengyuan Chen, Xiaogang Wang
American Journal of Computational Mathematics (AJCM) , 2013, DOI: 10.4236/ajcm.2013.31003
Abstract:

We present a new derivative-free optimization algorithm based on the sparse grid numerical integration. The algorithm applies to a smooth nonlinear objective function where calculating its gradient is impossible and evaluating its value is also very expensive. The new algorithm has: 1) a unique starting point strategy; 2) an effective global search heuristic; and 3) consistent local convergence. These are achieved through a uniform use of sparse grid numerical integration. Numerical experiment result indicates that the algorithm is accurate and efficient, and benchmarks favourably against several state-of-art derivative free algorithms.

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