用于腺苷检测的基于级联扩增核酸适体电化学传感界面的构建研究

该文报道了一种基于酶级联扩增的电化学核酸适体检测腺苷的新方法。当腺苷存在时,滚环扩增的引物通过E.coli DNA连接酶的作用与通过巯基组装在金电极上的固定探针连接。在pHi29 DNA聚合酶的作用下,滚环扩增反应进行并产生一条与环形探针完全互补的长的单链,然后将大量金纳米粒子标记的核酸探针与滚环扩增的产物杂交。该传感界面电化学行为的结果表明,通过酶级联扩增的方法提高了检测腺苷的阻抗响应灵敏度,且选择性和重现性良好。用于腺苷的检测时,其线性范围为2.0μmol/L~100μmol/L,最低检测浓度为2.0μmol/L,表明该传感界面的设计可作为一种通用方法而有望用于其它目标物的检测。     

An empirical molecular docking study of a di-iron binding protein with iron ions

Various molecular docking software packages are available for modeling interactions between small molecules and proteins.However,there have been few reports of modeling the interactions between metal ions and metalloproteins.In this study,the AutoDock package was employed to example docking into a di-iron binding protein,bacterioferritin.Each binding site of this protein was tested for docking with iron ions.Blind docking experiments showed that all docking conformations converged into two clusters,one for internal iron binding in sites within the metalloprotein and the other for external iron binding on the protein surface.Local docking experiments showed that there were significant differences between two internal iron binding sites.Docking at one site gave a reasonable root-mean-square deviation(RMSD) distribution with relatively low binding energy.Analysis of the binding mode quality for this site revealed that more than half of the docking conformations were categorized as having good binding geometry,while no good conformations were found for the other site.Further investigations indicated that coordinating water molecules contributed to the stability of binding geometries.This study provides an empirical approach towards the study of molecular docking in metalloproteins.     

现代施工企业业绩评价及价值管理探讨

施工企业的发展依赖于先进的企业管理,现代施工企业管理的有效工具是价值管理及业绩评价.施工企业传统的业绩评价一般以已经发生的经济业务及其成果作为衡量依据,具有短期性和滞后性;真正有价值的业绩评价应当面向企业的战略计划和未来发展方向,在企业业绩评价和考核中引入价值管理理念,实现企业价值最大化.     

浅淡数据挖掘技术及其相关问题解析

数据挖掘(DataMining,简称DM),又称数据库中的知识发现(Knowledge Discovery in Database,简称:KDD),是指从大型数据库或数据仓库中提取隐含的、未知的、特殊的及有潜在应用价值的信息或模式.本文在了解数据挖掘的定义和市场前景的基础上,结合当今企业对数据挖掘技术的重视和数据挖掘技术对企业发展带来的巨大效益的现状,从众多发面提出和分析了数据挖掘技术在发展和应用过程中面临的主要问题.     

Web数据挖掘在个性化推荐服务的应用

随着Internet的迅速发展和普及,人们在网络上开展的活动也越来越多,尤其是电子商务的兴起,使得网上购物逐渐成为一种时尚.然而由于互联网上的信息量日益增长,人们面对这些庞大的信息感到无所适从,花费大量时间在搜寻信息上,因此如何为用户提供更好的服务变得非常迫切.本文以数据挖掘理论为基础,分析和探讨了关联规则挖掘算法并应用该方法实现web个性化推荐服务.     

Editorial: Machine Learning and Intelligent Communications (MLICOM 2018)

Mobile Networks and Applications -     

Distributed algorithm for mixed equilibrium problems with event-triggered strategy

Neural Computing and Applications - A new iterative method based on the event-triggered strategy for finding a solution to a mixed equilibrium problem (MEP) is introduced in this paper. The target...