首页> 外文学位 >Making sense of microarray data: Development of an integrated bioinformatics tool.
【24h】

Making sense of microarray data: Development of an integrated bioinformatics tool.

机译:微阵列数据的意义:集成生物信息学工具的开发。

获取原文
获取原文并翻译 | 示例

摘要

Microarray technology promises to monitor interactions among tens of thousands of genes simultaneously. Two types of microarrays, Oligonucleotide (oligo) and cDNA arrays, are in common use. Oligo arrays have the advantage of providing a platform that can be more readily compared between laboratories. With rapid evolution of hardware and lab protocols, the challenge becomes the analysis of a vast amount of data rather than the manufacture or the use of microarrays. Most software applications were developed dealing with cDNA arrays. There remains a lack of tools that can be used for oligo array analysis. The goal of this research project is to develop a bioinformatics tool dedicated to analyzing oligo array data. Our tool, AffyMiner, consists of three functional components: GeneFinding---finding significant genes in the experiment, GOTree---constructing a Gene Ontology (GO) tree, and interfaces---linking to third-party applications. AffyMiner effectively deals with multiple replicates in the experiment, provides users flexibility of choosing different data metrics for finding significant genes, and is capable of incorporating various gene annotations. In addition, AffyMiner maps genes of interest onto the GO spaces, providing assistance in the interpretation of findings in the context of biology. Furthermore, AffyMiner provides a portal to use Cluster and GenMAPP, two popular programs for microarray analysis. AffyMiner has been used by multiple users and was found to be an effective tool that has reduced plenty of time and efforts needed for data analysis.
机译:微阵列技术有望同时监测成千上万个基因之间的相互作用。两种类型的微阵列,寡核苷酸(oligonucleotide,oligo)和cDNA阵列,是常用的。 Oligo阵列的优势在于提供了一个可以在实验室之间进行比较的平台。随着硬件和实验室协议的快速发展,挑战在于分析大量数据,而不是微阵列的制造或使用。大多数软件应用程序都是针对cDNA阵列开发的。仍然缺乏可用于寡核苷酸阵列分析的工具。该研究项目的目标是开发一种致力于分析寡核苷酸阵列数据的生物信息学工具。我们的工具AffyMiner包含三个功能组件:GeneFinding(在实验中查找重要的基因),GOTree(构建基因本体(GO)树)和接口(链接到第三方应用程序)。 AffyMiner有效地处理了实验中的多个重复项,为用户提供了选择不同数据指标以查找重要基因的灵活性,并且能够整合各种基因注释。此外,AffyMiner将感兴趣的基因映射到GO空间,为生物学背景下的发现解释提供帮助。此外,AffyMiner提供了一个门户网站,可使用Cluster和GenMAPP这两个流行的程序进行微阵列分析。 AffyMiner已被多个用户使用,被发现是一种有效的工具,它减少了数据分析所需的大量时间和精力。

著录项

  • 作者

    Lu, Guoqing.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Computer Science.
  • 学位 M.Sc.
  • 年度 2005
  • 页码 88 p.
  • 总页数 88
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号