ITR: Collaborative Research: New Approaches to Experimental Design and Statistical Analysis of Genomic and Structural Biologic Data from Multiple Sources

ITR：协作研究：多源基因组和结构生物学数据的实验设计和统计分析新方法

• 批准号: 0325544
• 负责人: Peter Doerschuk
• 金额: $ 79.2万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-10-01 至 2007-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0325544&HistoricalAwards=false
• 关键词: ITR; Collaborative; Research; New; Approaches

The biological sciences are advancing by posing increasingly complex and quantitative questions which require experiments that are increasingly complex procedures, and analysis of increasingly complex and large data sets. Information technology is pervasive throughout this process. Before beginning the laboratory work, computation is necessary for planning the experiment, and for later analysis of the results. In gene chip experiments for determining gene activity levels, planning issues include which biological hypotheses should be considered and what chemical conditions will yield the most informative results, followed by computation to reduce the collected data, which can be gigabytes of information, to forms that can be understood and exploited by biological scientists. In electron microscope experiments for determining the 3-D structure of viruses, planning issues include electron energy, defocus level, beam current, number of tilts, and tilt angles, followed by computation to reduce the measured data, which can be one hundred thousand or more images, to a biologically-plausible 3-D structure. Historically, insufficient attention has been devoted to the use of highly sophisticated information technology for quantitative planning and analysis of experiments, which jointly takes into account the behavior of the measurement apparatus, the goals of the experiment, the unavoidable uncertainty in the system, and the algorithmic complexity that a particular experimental design implies for the subsequent computational analysis of the experimental data. The research objective of this ITR project is to bring together a team of investigators from MIT, Purdue and NYU-Courant along with their industrial collaborators to apply principles from information, coding and systems theory, along with advanced computational methods for statistical inference and numerical optimization, to create a unified approach to planning and analysis of complex quantitative experiments in the biological sciences, such as the determination of gene expression using gene chips and the determination of 3-D viral structure from scattering and electron microscopy experiments. These biological problems will challenge the state of the art in information technology and an important characteristic of the project is the parallel development of new information technology and new biological applications. The human-resources objectives of this ITR project are to provide the opportunity for undergraduate students, graduate students, and postdoctoral associates to learn about and contribute to this exciting area at the interface between information technology and biological sciences. Because of the biological focus of the research it is anticipated that the proposed project will be an outstanding opportunity to recruit women and other underrepresented minorities into the Systems, Information and Computer Science endeavor.

生物科学不断提出越来越复杂和定量的问题，这些问题需要越来越复杂的实验程序以及越来越复杂和庞大的数据集的分析。 整个过程中信息技术无处不在。在开始实验室工作之前，需要进行计算来规划实验以及随后对结果进行分析。 在确定基因活性水平的基因芯片实验中，规划问题包括应考虑哪些生物学假设以及哪些化学条件将产生最具信息性的结果，然后进行计算以将收集到的数据（可能是千兆字节的信息）减少到可以的形式被生物科学家理解和利用。 在确定病毒3D结构的电子显微镜实验中，规划问题包括电子能量、散焦水平、束流、倾斜次数和倾斜角度，然后通过计算来减少测量数据，这些数据可以是十万或更多图像，形成生物学上合理的 3D 结构。 历史上，对于使用高度复杂的信息技术进行实验的定量规划和分析并没有给予足够的重视，这些技术共同考虑了测量设备的行为、实验的目标、系统中不可避免的不确定性以及特定实验设计对于实验数据的后续计算分析意味着算法的复杂性。 该 ITR 项目的研究目标是将来自麻省理工学院、普渡大学和 NYU-Courant 的研究人员团队及其工业合作者聚集在一起，应用信息、编码和系统理论的原理，以及用于统计推断和数值优化的先进计算方法，创建统一的方法来规划和分析生物科学中的复杂定量实验，例如使用基因芯片测定基因表达以及通过散射和电子显微镜实验测定 3D 病毒结构。这些生物学问题将挑战信息技术的最新水平，该项目的一个重要特点是新信息技术和新生物学应用的并行发展。该 ITR 项目的人力资源目标是为本科生、研究生和博士后提供机会，让他们了解信息技术和生物科学交叉领域的这一令人兴奋的领域并为其做出贡献。由于该研究的生物学重点，预计拟议的项目将是招募女性和其他代表性不足的少数群体参与系统、信息和计算机科学事业的绝佳机会。