课程文献中心 更多>>

关键词： Visual Search   Imaging Tool   Breast Screening   Inspection Time   Image Manipulation  

关键词： GENE-EXPRESSION PROFILES   BREAST-CANCER   PREOPERATIVE CHEMOTHERAPY   CYCLOPHOSPHAMIDE   FLUOROURACIL   CLASSIFIERS   DOXORUBICIN   PACLITAXEL   SIGNATURE   SURVIVAL  

摘要： Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

关键词： 深海放线菌   冷泉   多相分类  

摘要： 放线菌广泛分布于土壤中,因其具有产生抗生素等生物活性物质而被广泛研究。相关的陆源放线菌的研究报道很多,但海洋中放线菌的研究较少。本文使用选择性预处理方法从16个深海沉积物样品中选择性地分离获得400余株革兰氏阳性菌,主要分布于放线菌纲(Actinobacteria (class))的15个科的21个属和芽孢杆菌纲(Bacilli)的3个科的7个属,包括首次发现可从深海沉积物中分离到Geodermatophilus属、Janibacter属和Cellulomonas属的菌株及可能存在潜在新种13个。 分析了放线菌在不同沉积物种类和数量的不同。从热液环境中分离得到Geodermatophilus和Janibacter等属的菌株,讨论他们和深海热液活动区环境的关系;从结核区分离得到Williamsia属;从冷泉发现小单孢菌科的"Solwaraspora"和小单孢菌属的菌株,该科能产丰富的活性物质,是现在海洋放线菌研究领域的热点目标,极具研究价值,适合后续的开发和研究。 运用现代多相分类鉴定研究方法,对其中潜在的一株链霉菌属的新种和一株拟诺卡氏菌属的新种进行了形态学,生理生化特征,化学分类特征及分子分类的鉴定,确定了这两株放线菌的分类地位,并将其中一株链霉菌IH32-1命名为印度链霉菌(Streptomyces indica ***.)作为链霉菌属的新种进行了描述。

关键词： 食品   微生物   检验  

摘要： 微生物的分布很广泛,虽然它们对人类的生产生活有一定的积极作用,但它们也常常使工业器材受到腐蚀,使食品及原料腐败和变质,甚至以食物作媒介引起人体中毒、染病、致癌和死亡。本文在此就食品微生物的检验意义及作用进行了分析。

关键词： Acceptance   Macroevolution   Understanding  

摘要： The goal of this research was to illuminate the relationship between students' acceptance and understanding of macroevolution. Our research questions were: (1) Is there a relationship between knowledge of macroevolution and acceptance of the theory of evolution?; (2) Is there a relationship between the amount of college level biology course work and acceptance of evolutionary theory and knowledge of macroevolution?; and (3) Can college student acceptance of the theory of evolution and knowledge of macroevolution change over the course of a semester? The research participants included 667 students from a first-semester biology course and 74 students from the evolutionary biology course. Data were collected using both the MATE (a measure of the acceptance of evolutionary theory) and the MUM (a measure of understanding of macroevolution). Pre-instruction data were obtained for the introductory biology course, and pre- and post-data were obtained for the evolutionary biology course. Analysis revealed acceptance of evolution (as measured by the MATE) was correlated to understanding of macroevolution, and the number of biology courses was significantly correlated to acceptance and knowledge of macroevolution. Finally, there was a statistically significant change in students' understanding of macroevolution and acceptance of evolution after the one-semester evolutionary biology course. Significance of these findings is discussed. © 2010 Springer Science+Business Media, LLC.

关键词： 侵权责任   违约责任   请求权竞合  

摘要： 我国《合同法》第122条规定侵权责任和违约责任竞合的处理方式,即在出现竞合的情形时,只允许受害人选择其中一项请求权提出请求,这在世界各国的合同法中也是少见的,但在某些情况下这种方式却不能完全赔偿受害人的损失。因此,根据现代民法精神原则的指导,应重新定义侵权责任和违约责任竞合的概念,并依据两种请求权所请求的利益的不同形态,允许受害人自由选择一种或两种请求权,从而使当事人的损失能得到完全的赔偿。

关键词： 标准化   检验检疫   模式创新  

摘要： 标准化工作是检验检疫工作的重要组成部分和综合性基础工作,检验检疫模式创新是质检持续发展的基石和动力,对于检验检疫部门来说,面对大幅提升的工作量,如何通过充分发挥标准化对检验检疫模式创新的作用,既实现有效检验监管和又能不断提升服务水平,实现标准化与检验检疫模式创新的统一,进而达到维护国家经济安全、确保进出口产品质量安全,保障检验检疫工作需要的目的。本文认为,标准化是检验检疫模式创新的技术基础平台,标准化对检验检疫模式创新既有积极的引导作用,同样模式创新对标准化又有反作用,正确认识标准化对检验检疫模式创新的作用,尤其应该引起检验检疫工者的重视。

关键词： Generalized VC dimensions   Multi-class support vector machines   Rademacher complexity   Sample complexity   CLASSIFICATION  

摘要： Bounds on the risk play a crucial role in statistical learning theory. They usually involve as capacity measure of the model studied the VC dimension or one of its extensions. In classification, such oVC dimensionso exist for models taking values in {0, 1}, [[1, Q]], and . We introduce the generalizations appropriate for the missing case, the one of models with values in Q. This provides us with a new guaranteed risk for M-SVMs. For those models, a sharper bound is obtained by using the Rademacher complexity.

关键词： CLASS PREDICTION   EXPRESSION DATA   DISCOVERY   FEATURES   CANCER   ALGORITHMS   PATTERNS   NUMBER  

摘要： Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are commonly with extremely high feature-to-sample ratio. In addition to the essential objectives such as to reduce data noise, to reduce data redundancy, to improve sample classification accuracy, and to improve model generalization property, feature selection also helps biologists to focus on the selected genes to further validate their biological hypotheses. Results: In this paper we describe an improved hybrid system for gene selection. It is based on a recently proposed genetic ensemble (GE) system. To enhance the generalization property of the selected genes or gene subsets and to overcome the overfitting problem of the GE system, we devised a mapping strategy to fuse the goodness information of each gene provided by multiple filtering algorithms. This information is then used for initialization and mutation operation of the genetic ensemble system. Conclusion: We used four benchmark microarray datasets (including both binary-class and multi-class classification problems) for concept proving and model evaluation. The experimental results indicate that the proposed multi-filter enhanced genetic ensemble (MF-GE) system is able to improve sample classification accuracy, generate more compact gene subset, and converge to the selection results more quickly. The MF-GE system is very flexible as various combinations of multiple filters and classifiers can be incorporated based on the data characteristics and the user preferences.