CAREER: Sparse-sampling inference for functional proteomics, metabolomics and ionomics

普渡大学获得了美国国家科学基金会（NSF）教师早期职业发展（CAREER）项目的资助，用于开发功能蛋白质组学、代谢组学和基因组学的统计和计算工具。拟议的研究将解决三个相互关联的目标：(1)从高通量实验中准确鉴定和定量蛋白质，代谢物和离子，这些实验以质量和核磁共振谱的形式产生稀疏数据；(2)稀疏异构数据集的联合解释与集成；(3)全局定向后续实验优化设计。该方案的创新之处在于它紧密结合了蛋白质组学、代谢组学和离子组学的生物学和技术特征。因此，它将增加调查解释的敏感性、准确性和范围。开发的统计推断方法和相关开源软件的效用将在酿酒葡萄球菌的功能屏幕上进行演示，该功能屏幕整合了异质转录组学、蛋白质组学、代谢组学和离子组学数据集。该计划将有助于弥合生物学家、化学家和统计学家之间的沟通鸿沟。该项目将通过提供与用户社区相关的案例研究，通过在普渡大学的科学会议和跨学科课程中提供跨学科教程和短期课程，以及通过为跨部门的研究生和本科生提供指导，促进计算思维和统计方法的适当使用。与这些活动相关的材料可在www.stat.purdue.edu/~ovitek上获得

Purdue University is awarded a grant by the NSF Faculty Early CareerDevelopment (CAREER) Program to develop statistical and computationaltools for functional proteomics, metabolomics and ionomics. Theproposed research will address three inter-related aims: (1) Accurateidentifications and quantifications of proteins, metabolites and ionsfrom high-throughput experiments, which generate sparse data in formof mass and nuclear magnetic resonance spectra; (2) Jointinterpretation and integration of these sparse heterogeneous datasets;and (3) Optimal design of global and targeted follow-up experiments.The proposed program is innovative in that it closely accounts for thebiological and technological characteristics of proteomics,metabolomics and ionomics. As the result, it will increase thesensitivity, accuracy, and scope of interpretation of theinvestigations. The utility of the developed methods of statisticalinference, and of the associated open-source software, will bedemonstrated on functional screens of S. cerevisiae, which integrateheterogeneous transcriptomic, proteomic, metabolomic and ionomicdatasets. The proposed program will contribute to bridging the communication gapbetween biologists, chemists and statisticians. The project will promote thecomputational thinking, and the appropriate use of statisticalmethodology, by making available case studies that are relevant to theuser community, by offering interdisciplinary tutorials and shortcourses at scientific meetings and interdisciplinary courses atPurdue, and by providing mentoring for graduate and undergraduate students acrossdepartments. Materials associated with these activities will beavailable at www.stat.purdue.edu/~ovitek