Splicing-site recognition of rice (Oryza sativa L.)DNA sequences by support vector machines

Motivation: It was found that high accuracy splicing-site recognition of rice (Oryza sativa L.) DNA sequence is especially difficult. We described a new method for the splicing-site recognition of rice DNA sequences. Method: Based on the intron in eukaryotic organisms conforming to the principle of GT-AG, we used support vector machines (SVM) to predict the splicing sites. By machine learning, we built a model and used it to test the effect of the test data set of true and pseudo splicing sites. Results: The prediction accuracy we obtained was 87.53% at the true 5' end splicing site and 87.37% at the true 3' end splicing sites. The results suggested that the SVM approach could achieve higher accuracy than the previous approaches.     

Presidential rhetoric's visual turn: Performance fragments and the politics of illusionism

This essay explores the aesthetic and rhetorical implications of prudent and imprudent presidential performance fragments embodied in photo‐opportunities, thereby addressing presidential rhetoric's “visual turn. “Assembled as a critical rhetoric text, this essay posits that presidential performance fragments privilege the dominant ideology and its power relationships. In addition, this project argues that prudent presidential performances signal a chief executive's consubstantiality with the mythic presidency, centralized authority, and active political leadership. Imprudent photo‐opportunity performances, by contrast, impact negatively a president's image, agenda, credibility, and authority. The essay concludes with a discussion of how political images symbolically affect the citizenry and democratic processes, and advances foundational issues for the critic.     

Splicing-site recognition of rice (<Emphasis Type="Italic">Oryza sativa</Emphasis> L.) DNA sequences by support vector machines

Motivation: It was found that high accuracy splicing-site recognition of rice (Oryza sativa L.) DNA sequence is especially difficult. We described a new method for the splicing-site recognition of rice DNA sequences. Method: Based on the intron in eukaryotic organisms conforming to the principle of GT-AG, we used support vector machines (SVM) to predict the splicing sites. By machine learning, we built a model and used it to test the effect of the test data set of true and pseudo splicing sites. Results: The prediction accuracy we obtained was 87.53% at the true 5′ end splicing site and 87.37% at the true 3′ end splicing sites. The results suggested that the SVM approach could achieve higher accuracy than the previous approaches. Project partially supported by the Start-up Funding of Zhejiang University to Chen Liang-biao     

Screen p53 mutations in hepatocellular carcinoma by FASAY:A novel splicing mutation

INTRODUCTION Hepatocellular carcinoma (HCC) is the sixth most common cancer in new cases per year (626 000) and the third most common cancer resulting in death (598 000) (Parkin et al., 2005). China is the country most seriously suffering from HCC, accounting for 55% of total cases and deaths worldwide per year. The clinical behavior of HCC is heterogeneous and difficult to predict, and in patients undergoing resec-tion, recurrence rates can be as high as 50% in two years and life ex…     

基于聚类分析的规则文字碎片拼接技术研究

针对目前国内外鲜有关于规则文字碎片拼接技术的研究问题,本文基于聚类分析方法及matlab程序设计提出了一种用于解决此问题的方法。对于规则文字碎片,利用图像的像素值矩阵进行分析,通过对各个碎片的边缘像素值向量进行聚类,借助最小距离进行边缘匹配,实现规则文字碎片的拼接。实验证明,该方法能够有效实现规则文字碎片的拼接。     

元小说"碎片化"写作:颠覆传统叙述的整体性

"元小说"是作家以小说的形式对传统小说艺术进行自我反思的结果,"碎片化"叙述是元叙述解构现实主义写作成规的叙述语言变异之一,它颠覆了传统叙述的整体性并进而消解这一叙述模式背后的意识形态.文章以马原等先锋派作家作品为例,依据当代学者的研究成果推导出元小说叙述迥异于中国传统文学创作的碎片化叙述语言变异特征.