Gene Expression

基因表达

基本信息

批准号：
7826835
负责人：
LESLEYANN HAWTHORN
金额：
$ 19.22万
依托单位：
ROSWELL PARK CANCER INSTITUTE CORP
依托单位国家：
美国
项目类别：
财政年份：
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/7826835
关键词：
Algorithms Alleles Alternative Splicing Arts Award Bioinformatics Biometry Books Budgets Buffaloes Cancer Center Support Grant Categories Cells Chromosomal Loss Chromosome abnormality Chromosomes Collaborations Communities Complex Computer software Consultations CpG Islands Custom DNA DNA Sequence DNA-Protein Interaction Data Data Analyses Data Set Detection Development Disease Doctor of Philosophy Electrophoresis Emerging Technologies Ensure Event Exons Funding Gene Expression Gene Expression Microarray Analysis Gene Expression Profiling Generations Genes Genetic Genetic Polymorphism Genome Genomics Genotype Glass Gold Grant Hawthorn plant Head Human Individual Investigation Karyotype determination procedure Label Loss of Heterozygosity Maintenance Maps Methylation Microarray Analysis Mutation Mutation Analysis Nucleotides Oligonucleotides Organism Overlapping Genes Peer Review Pharmaceutical Preparations Polymorphism Analysis Population Positioning Attribute Preparation Procedures Process Publications Quality Control RNA Research Research Infrastructure Research Personnel Resolution Resources Rewards Role Roswell Park Cancer Institute Running Sampling Scanning Scheme Sequence Analysis Services Site Solutions Specificity Spectrophotometry Staining method Stains Surface System Technology Testing Time Tissues Training Training Support Transcript Translating Universities Update Validation Variant Virus Work base chromatin immunoprecipitation cost density design gel electrophoresis genetic association genetic linkage analysis genome wide association study genome-wide innovation instrument member mitochondrial genome new technology novel programs promoter research study response success tool validation studies

项目摘要

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.

成功招募了基因表达资源（GER） Lesleyann Hawthorn 博士，2001 年。自那时以来，该资源蓬勃发展，拥有广泛的基础满意的用户的持续惠顾源于独特的微阵列方法实验。它的成功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具有数据分析的附加优势，以便将结果提供给个人与大多数基于阵列的设施不同，研究人员采用的是可用的格式。 Hawthorn 博士和 GER 工作人员保持紧跟新兴技术，为用户提供广泛的专业知识和选择。这次成功得到了庞大的用户群、出版物和授予的资助的证实。资源按功能划分进入基因组水平的基因表达、基因分型和拷贝数分析。在水平单个染色体区域或特定基因，提供突变/多态性分析、SNP 验证甲基化状态的发现、表达水平定量和分析。最重要的是，资源为其支持的所有平台提供数据分析，并提供专业知识、时间和资金用于新技术的开发。例如，外显子阵列分析已被开发出来，允许同时检测基因表达和选择性剪接事件。此外， Resource 现在能够运行全基因组平铺阵列，从而实现最高分辨率的片上芯片分析以及基因组 DNA 中新转录本的检测。在过去的几年里， Resource 一直致力于研究基因组数据分析的创新方法。其中之一以高密度 SNP 阵列为中心，提供最高密度的基因分型，以及同步 CGH 分析以及伴随的 LOH 分析。 Gene Expression 一直在使用这些数组来寻找染色体区域（CGH）的增加和损失。 SNP 定位阵列检测标准的能力细胞遗传学异常代表了传统核型分析的重大进步。 GER 有与 Cowell 博士的团队 (GN) 合作开发统计分析工具，允许基因叠加表达数据与 aCGH 数据相结合，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该资源。该资源有助于加强同行评审的资助、出版物和招聘工作。预计随着新 CSBT 计划（Gudkov 博士）、MTET 计划（Adjei 博士）和 Til（Lee 博士）的招募资源将会扩大。该资源被所有六个计划使用，98% 的用户是 CCSG 成员。请求 CCSG 支持 80,355 美元，占总运营预算的 11%。