首页> 外文学位 >Bioinformatic techniques in Drosophila circadian biology: An interdisciplinary approach to gene discovery and behavior analysis of the circadian clock of Drosophila melanogaster.
【24h】

Bioinformatic techniques in Drosophila circadian biology: An interdisciplinary approach to gene discovery and behavior analysis of the circadian clock of Drosophila melanogaster.

机译:果蝇昼夜节律生物学中的生物信息学技术:一种跨学科方法,用于研究果蝇昼夜节律时钟的基因发现和行为分析。

获取原文
获取原文并翻译 | 示例

摘要

Drosophila melanogaster has long been utilized as a means to obtain understanding of the circadian clock. While a great deal is known with respect to the core elements of this biological timing mechanism, relatively little is known about the various afferent pathways that allow it to respond to changes in the environment, and the efferent pathways through which it is able to effect regulation of the biomolecular and eventual behavioral outputs of the circadian clock. The discovery of genes that function in these pathways is critical to placing current knowledge of the core clock mechanism in its biological context, as the central hub of an extremely complex signaling network that regulates an enormous amount of animal behavior. Two bioinformatic approaches are presented as a means to facilitate such discovery. One focuses on analysis of microarray data to indentify transcripts that exhibit cyclic expression, a hallmark of many currently known circadian genes (Chapters 1-3). The second presents a computational tool that can be used to greatly improve the throughput of screens that seek to identify novel circadian mutants through the automated characterization of their behavior (Chapter 4).
机译:果蝇(Drosophila melanogaster)长期以来被用作了解生物钟的手段。尽管人们对这种生物定时机制的核心要素知之甚少,但对于使它对环境变化做出反应的各种传入途径及其能够进行调节的传入途径知之甚少昼夜生物钟的生物分子和最终行为输出。在这些途径中起作用的基因的发现对于将当前关于核心时钟机制的知识置于其生物学环境中至关重要,因为它是调控大量动物行为的极其复杂的信号网络的中心枢纽。提出了两种生物信息学方法,作为促进这种发现的手段。其中一个重点是分析微阵列数据以鉴定表现出循环表达的转录本,这是许多当前已知的昼夜节律基因的标志(第1-3章)。第二部分介绍了一种计算工具,该工具可用于通过自动表征其生物钟行为来鉴定新的昼夜节律突变体,从而大大提高筛选的通量(第4章)。

著录项

  • 作者

    Keegan, Kevin Patrick.;

  • 作者单位

    Northwestern University.;

  • 授予单位 Northwestern University.;
  • 学科 Biology Biostatistics.;Biology Neuroscience.;Biology Bioinformatics.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 163 p.
  • 总页数 163
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物数学方法;神经科学;
  • 关键词

  • 入库时间 2022-08-17 11:38:19

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