Microsatellite markers have become one kind of the most important molecular tools used in various researches. A large number of microsatellite markers are required for the whole genome survey in the fields of molecula...Microsatellite markers have become one kind of the most important molecular tools used in various researches. A large number of microsatellite markers are required for the whole genome survey in the fields of molecular ecology,quantitative genetics and genomics. Therefore,it is extremely necessary to select several versatile,low-cost,efficient and time-and labor-saving methods to develop a large panel of microsatellite markers. In this study,we used Zhikong scallop(Chlamys farreri) as the target species to compare the efficiency of the five methods derived from three strategies for microsatellite marker development. The results showed that the strategy of constructing small insert genomic DNA library resulted in poor efficiency,while the microsatellite-enriched strategy highly improved the isolation efficiency. Although the mining public database strategy is time-and cost-saving,it is difficult to obtain a large number of microsatellite markers,mainly due to the limited sequence data of non-model species deposited in public databases. Based on the results in this study,we recommend two methods,microsatellite-enriched library construction method and FIASCO-colony hybridization method,for large-scale microsatellite marker development. Both methods were derived from the microsatellite-enriched strategy. The experimental results obtained from Zhikong scallop also provide the reference for microsatellite marker development in other species with large genomes.展开更多
In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representat...In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.展开更多
The purpose of this paper is to create a comprehensive analysis of the development of foreign trade in the global world, the process of divergence of exports and imports under the influence political and economic chan...The purpose of this paper is to create a comprehensive analysis of the development of foreign trade in the global world, the process of divergence of exports and imports under the influence political and economic changes in Europe and the economic crisis in the world. Data from world public databases are summarized to a clear and understandable form. We analyzed the share of imports and exports （due to the global trade is presented） and its potential impact on the development of current account balance （CAB） for the United States of America （USA）, the European Union （EU）, and China. Correlation coefficient timeline for the last decade of CAB and world trade is also presented to show the influence of trade flow in the world and the EU with respect to current account. The work emphasizes the clear and understandable processing of the required data, which are then formulated to make arguments and then used to make predictions of further development of world trade. From summarized data, future crisis can be predicted and impacts can be evaluated.展开更多
基金supported by ‘863’ Program (2006AA10A408 and 2006AA10A411), NSFC30571417, NYHYZX07-047, 2005DKA30470, 2006BAD09A10 and NCET-06-0594.
文摘Microsatellite markers have become one kind of the most important molecular tools used in various researches. A large number of microsatellite markers are required for the whole genome survey in the fields of molecular ecology,quantitative genetics and genomics. Therefore,it is extremely necessary to select several versatile,low-cost,efficient and time-and labor-saving methods to develop a large panel of microsatellite markers. In this study,we used Zhikong scallop(Chlamys farreri) as the target species to compare the efficiency of the five methods derived from three strategies for microsatellite marker development. The results showed that the strategy of constructing small insert genomic DNA library resulted in poor efficiency,while the microsatellite-enriched strategy highly improved the isolation efficiency. Although the mining public database strategy is time-and cost-saving,it is difficult to obtain a large number of microsatellite markers,mainly due to the limited sequence data of non-model species deposited in public databases. Based on the results in this study,we recommend two methods,microsatellite-enriched library construction method and FIASCO-colony hybridization method,for large-scale microsatellite marker development. Both methods were derived from the microsatellite-enriched strategy. The experimental results obtained from Zhikong scallop also provide the reference for microsatellite marker development in other species with large genomes.
基金Supported by the National Natural Science Foundation of China(No.61379014)
文摘In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.
文摘The purpose of this paper is to create a comprehensive analysis of the development of foreign trade in the global world, the process of divergence of exports and imports under the influence political and economic changes in Europe and the economic crisis in the world. Data from world public databases are summarized to a clear and understandable form. We analyzed the share of imports and exports （due to the global trade is presented） and its potential impact on the development of current account balance （CAB） for the United States of America （USA）, the European Union （EU）, and China. Correlation coefficient timeline for the last decade of CAB and world trade is also presented to show the influence of trade flow in the world and the EU with respect to current account. The work emphasizes the clear and understandable processing of the required data, which are then formulated to make arguments and then used to make predictions of further development of world trade. From summarized data, future crisis can be predicted and impacts can be evaluated.
