PostDoctoral Research Fellowship in Biological Informatics FY2006

2006 财年生物信息学博士后研究奖学金

• 批准号: 0630780
• 负责人: Elizabeth Purdom
• 金额: $ 12万
• 依托单位: Purdom Elizabeth
• 依托单位国家: 美国
• 项目类别: Fellowship
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-03-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0630780&HistoricalAwards=false
• 关键词: PostDoctoral; Research; Fellowship; Biological; Informatics

Project Title: "Statistical Methods for the Combined Analysis of Biological Networks and Large Data Sets" This project is awarded under the Postdoctoral Research Fellowships in Biological Informatics Program for 2006. The research develops statistical methods to better incorporate the many different sources of data available in biology into a single coherent analysis. In particular, the research focuses on using biological information that is represented visually as a network or graph as an aid to analyzing the massive amounts of data collected in high throughput experiments. By incorporating the information from the network, the analysis of the experiments will be more biologically relevant and also better explain the complexities of the biological system as a whole. The research will make use of statistical learning tools, in particular kernel methods, as well as other statistical procedures for multiple testing and estimation. The training goals of this fellowship are to develop skills for interfacing between statistics and biology -- an important part of which will be developing collaborations with biologists. The research will be carried out in the lab of Sandrine Dudoit at the University of California, Berkeley where the fellow will gain experience in compiling networks and other information from large biological databases and in implementing and disseminating software code to other researchers.

项目名称：“生物网络与大数据集组合分析之统计方法”本研究项目为2006年度生物资讯学博士后研究金。该研究开发了统计方法，以更好地将生物学中可用的许多不同数据来源纳入一个单一的连贯分析。特别是，该研究侧重于使用以网络或图形形式直观表示的生物信息，以帮助分析在高通量实验中收集的大量数据。通过整合来自网络的信息，实验的分析将更具生物相关性，并更好地解释整个生物系统的复杂性。该研究将利用统计学习工具，特别是核方法，以及其他统计程序进行多重测试和估计。该研究金的培训目标是发展统计学和生物学之间的接口技能-其中一个重要部分将是发展与生物学家的合作。这项研究将在加州大学伯克利分校的Sandrine Dudoit实验室进行，该研究员将获得从大型生物数据库中编译网络和其他信息以及向其他研究人员实施和传播软件代码的经验。