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中文摘要
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核心C基因表达分析的目的是为项目提供高度的 需要专门的方法学:(1)从人和动物样本中提取高质量的RNA 并进行质量控制测试;(2)加工RNA以生产高质量的标记cRNA 杂交到微阵列;(3)提供必要的图像采集和数据挖掘软件 分析微阵列技术产生的海量基因表达数据;(4) 执行针对每个项目量身定做的数据分析;以及(5)通过以下方式量化mRNA水平 TaqMan实时定量聚合酶链式反应检测微阵列筛选出的基因。基因表达 分析核心在Affymetrix微阵列数据分析方面拥有丰富的专业知识,使用不同的 用于数据挖掘的方法和计算工具,尤其是从肺部获取的样本 通过支气管镜/刷检和支气管肺泡灌洗对人体志愿者进行检查。核心在它的核心 处置Affymetrix基因芯片设备,以及最先进的软件包 可通过威尔康奈尔计算生物医学研究所获得。TaqMan实时 RT-PCR通过这个核心可用于RNA定量,使用高通量96良好应用 生物系统7500和软件,为感兴趣的基因设计特定的引物,以及 在每个项目中协助调查员开展的技术支持和培训 TaqMan分析。核心将为所有五个项目投入同等的资源。
英文摘要
The purpose of Core C - Gene Expression Analysis is to provide the projects with the highly specialized methodology required to: (1) extract high quality RNA from human and animal samples and perform quality control tests; (2) process RNA to produce high quality labeled cRNA for hybridization to the microarrays; (3) provide image capture and data mining software necessary for analyzing the vast amount of gene expression data generated by microarray technology; (4) perform data analysis tailored for each individual project; and (5) to quantify mRNA levels by TaqMan real time PCR for the genes selected by the microarray screen. The Gene Expression Analysis Core has extensive expertise in Affymetrix microarray data analysis using different methods and computational tools for data mining, particularly of samples obtained from the lungs of human volunteers by bronchoscopy/brushing, and bronchoalveolar lavage. The Core has at its disposal the Affymetrix GeneChip equipment, as well as state-of-the-art software packages that are available through the Weill Cornell Institute for Computational Biomedicine. TaqMan real-time RT-PCR for RNA quantitation is available through this Core, using high throughput 96 well Applied Biosystems 7500 and software to design specific primers for the genes of interest, as well as technical support and training to assist the investigators in each of the projects to carry out TaqMan analysis. The Core will devote equal resources to all five projects.
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Core 1: Genomics Core
Core 1: Genomics Core
Core 1: Genomics Core
The PacBio Sequel for Single Molecule, Real-Time, Long Read Sequencing
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