PostDoctoral Research Fellowship in Biological Informatics FY2006

项目名称：“结合分析生物网络和大数据集的统计方法”该项目是2006年生物信息学博士后研究奖学金获得者。这项研究开发了统计方法，以便更好地将生物学中可用的许多不同数据来源合并到一个单一的连贯分析中。特别是，这项研究的重点是使用视觉上表示为网络或图形的生物信息来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，对实验的分析将具有更多的生物学相关性，并作为一个整体更好地解释生物系统的复杂性。这项研究将利用统计学习工具，特别是核心方法，以及其他统计程序进行多次测试和估计。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桑德林·杜杜伊特的实验室进行，在那里，这位研究员将获得从大型生物数据库编译网络和其他信息以及实现软件代码并将其传播给其他研究人员的经验。

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.