DNA & PROTEIN MICRO-ARRAY FACILITY (SHARED RESOURCE)

UCI DMA和蛋白质微阵列设备最初成立于1999年，是一家综合性癌症公司 中心共享资源核心设施，旨在协助南北校区调查人员 进行微阵列表达分析。南校区内外约200名调查人员 在过去五年期间提供了服务。我们主要利用Affymetrix基因芯片阵列 用于监测基因表达和进行SNP/基因定位的系统。我们的任务是提供核糖核酸 以一致和及时的方式进行最高质量的表达和基因组DMA分析 我们设施的用户。除了提供进行基因表达和 SNP/基因作图协议，工作人员提供关于实验设计的建议和咨询，以及 基于微阵列的研究的数据分析方法和统计。 目前，这项技术的主要用途是确定基因的差异表达模式， 无论是在细胞内还是组织内。这项技术使研究人员能够比较 病变细胞和正常细胞、癌细胞和非癌细胞以及不同组织类型。的目标是 这些类型的研究是为了更好地理解可能导致疾病状态的过程，并 找到新的或更好的方法来控制或阻止疾病状态的进展。一个迅速的 越来越多的人使用这项技术分析基因类型变异(SNPs)，以绘制致病基因的图谱。 这些类型的方法将提供对多因素疾病状态的洞察。全基因组信息 与个体不同，基因信息可以用来理解由 多个基因或环境和遗传因素的共同作用。 由于全基因组阵列提供了大量的详细信息，很可能 微阵列不仅将成为了解疾病过程的更重要的工具，而且还将成为 在疾病诊断和个性化治疗的设计方面。

The UCI DMA & Protein MicroArray Facility was initially established in 1999 as a Comprehensive Cancer Center Shared Resource Core Facility, directed at assisting both North and South Campus investigators performing microarray expression analysis. About 200 investigators inside and outside the South Campus have been provided services in the last five year period. We primarily utilize the Affymetrix GeneChip array system to monitor gene expression and perform SNP/genotype mapping. Our mission is to provide RNA expression and genomic DMA analysis in a consistent and timely manner that is of the highest quality for all of our Facility's users. In addition to providing experimental expertise for performing gene expression and SNP/genotype mapping protocols, the staff provides advice and consultation on experimental design, and data analysis approaches and statistics for microarray based research. Currently, the primary use of this technology is to determine the differential expression patterns of genes, either within cells or tissues. This technology enables investigators to compare patterns of expression in diseased and normal cells, cancer cells and non-cancerous cells and in different tissue types. The goal of these types of studies is to better understand the processes that potentially lead to diseased states and to find new or better ways of either controlling or stopping the progression of diseased states. A rapidly increasing use of this technology is analysis of genotypic variants (SNPs) to map disease-causing genes. These types of approaches will provide insight into multifactorial disease states. Genomewide information unlike individual gene information can be used to understand the more subtle patterns of diseases caused by multiple genes or by the confluence of environmental and genetic factors. Because of the great amount of detailed information provided from genomewide arrays, it is likely that microarrays will become an even more important tool not only in understanding disease processes, but also in disease diagnosis and the design of individualized therapies.