Gene Expression

基因表达

• 批准号: 8637140
• 负责人: LESLEYANN HAWTHORN
• 金额: $ 376.34万
• 依托单位: ROSWELL PARK CANCER INSTITUTE CORP
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8637140
• 关键词: Algorithms; Alleles; Alternative Splicing; Award; Bioinformatics; Budgets; Buffaloes; Cancer Center Support Grant; Categories; Cells; ChIP-on-chip; Chromosomal Loss; Chromosome abnormality; Chromosomes; Communities; Complex; Computer software; Custom; DNA; Data; Data Analyses; Data Set; Detection; Development; Disease; Doctor of Philosophy; Electrophoresis; Emerging Technologies; Ensure; Event; Exons; Funding; Gene Expression; Gene Expression Profiling; Genes; Genetic; Genome; Genomics; Genotype; Grant; Hawthorn plant; Individual; Karyotype determination procedure; Label; Loss of Heterozygosity; Maps; Methylation; Mutation; Organism; Peer Review; Pharmaceutical Preparations; Polymorphism Analysis; Population; Preparation; Procedures; Process; Publications; Quality Control; RNA; Research; Research Infrastructure; Research Personnel; Resolution; Resources; Roswell Park Cancer Institute; Running; Sampling; Scanning; Sequence Analysis; Services; Single Nucleotide Polymorphism Map; Solutions; Spectrophotometry; Staining method; Stains; Technology; Testing; Time; Tissues; Training; Transcript; Translating; Universities; Update; Validation; Work; base; cost; density; design; gel electrophoresis; genetic association; genetic linkage; genome wide association study; genome-wide; innovation; member; new technology; novel; programs; research study; response; success; tool

The Gene Expression Resource (GER) was established with the successful recruitment of Lesleyann Hawthorn, PhD in 2001. The Resource has flourished since that time with a broad base of satisfied users whose continued patronage is derived from a unique approach to microarray experimentation. Its success is largely due to a commitment to provide researchers with high-quality microarray data with the added advantage of data analysis so that the results provided to the individual researchers are in a usable format, unlike most array-based facilities. Dr Hawthorn and the GER staff keep abreast of emerging technologies to provide users with a broad range of expertise and options. This success is substantiated by a large user base, publications and awarded grants. The Resource is functionally divided into Gene Expression, Genotyping, and Copy Number Analysis at the genomics level. At the level of individual chromosomal regions or specific genes, it offers mutation/polymorphism analysis, SNP validation and discovery, expression level quantification and analysis of methylation status. Most importantly, the Resource offers data analysis for all the platforms that it supports and provides expertise, time and funding for the development of novel technologies. For example, Exon array analysis has been developed which allows simultaneous detection of gene expression and alternative splicing events. Furthermore, the Resource is now able to run Whole-Genome Tiling arrays, which permit the highest-resolution Chip-on-Chip analysis as well as the detection of novel transcripts in genomic DNA. During the last few years, the Resource has been working on innovative approaches to the analysis of genomics data. One of these centers on the high-density SNP arrays that offer the highest density genotyping, as well as simultaneous CGH analysis with accompanying LOH analysis. Gene Expression has been using these arrays to look for gains and losses of chromosomal regions (CGH). The ability of the SNP Mapping arrays to detect standard cytogenetic abnormalities represents a major advancement over conventional karyotyping. The GER has collaborated with Dr Cowell's group (GN) to develop statistical analysis tools that permit the overlay of gene expression data with aCGH data, thus enhancing the power of both these technologies. Members of the six CCSG programs utilized this Resource over the last project period. The Resource was instrumental in enhanced peer-reviewed funding, publications and recruitment efforts. It is anticipated that with the new recruitment into the CSBT Program (Dr Gudkov), MTET Program (Dr Adjei), and Til (Dr Lee) the utilization of the Resource will expand. The Resource is used by all six Programs and 98% of users are CCSG members. $80,355 in CCSG support is requested, representing 11% of the total operating budget.

基因表达资源（格尔）的建立与成功招募 Lesleyann山楂，2001年博士。自那时以来，该资源蓬勃发展，具有广泛的基础， 满意的用户，他们的持续赞助来自于对微阵列的独特方法 实验它的成功在很大程度上归功于致力于为研究人员提供高质量的 微阵列数据与数据分析的附加优势，使得提供给个体的结果 研究人员是在一个可用的格式，不像大多数基于阵列的设施。山楂博士和格尔的工作人员 与新兴技术并驾齐驱，为用户提供广泛的专业知识和选择。这一成功 庞大的用户群、出版物和获得的赠款证实了这一点。资源按功能划分 在基因组学水平的基因表达，基因分型和拷贝数分析。一级 单个染色体区域或特定基因，它提供突变/多态性分析，SNP验证 以及甲基化状态的发现、表达水平定量和分析。最重要的是 Resource为其支持的所有平台提供数据分析，并提供专业知识、时间和资金 用于开发新技术。例如，已经开发了外显子阵列分析，其 允许同时检测基因表达和可变剪接事件。而且 资源现在能够运行全基因组拼接阵列，允许最高分辨率的芯片上芯片 分析以及检测基因组DNA中的新转录物。在过去的几年里， Resource一直致力于研究基因组学数据分析的创新方法。其中一 中心的高密度SNP阵列，提供最高密度的基因分型，以及同时 CGH分析和伴随的洛缺失分析。基因表达公司一直在使用这些阵列来寻找 染色体区域的获得和丢失（CGH）。SNP作图阵列检测标准品的能力 细胞遗传学异常代表了相对于常规核型分析的重大进步。德国格尔已经 与考威尔博士的小组（GN）合作开发了统计分析工具， 表达数据与aCGH数据，从而增强了这两种技术的能力。六人组成员 CCSG计划在上一个项目期间利用了此资源。该资源有助于 加强同行审查的供资、出版物和征聘工作。预计随着新的 招募到CSBT计划（古德科夫博士），MTET计划（阿杰博士），和蒂尔（李博士）的利用 资源将扩大。该资源被所有六个程序使用，98%的用户是CCSG 成员要求CCSG支持80，355美元，占总业务预算的11%。