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

普渡大学获得了NSF教师早期职业发展(CALEAR)计划的资助，用于开发功能蛋白质组学、代谢组学和离子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)准确鉴定和量化来自高通量实验的蛋白质、代谢物和离子，这些实验产生质量和核磁共振光谱形式的稀疏数据；(2)结合这些稀疏的异质数据集的解释和整合；以及(3)全球和有针对性的后续实验的优化设计。该计划的创新之处在于它紧密考虑了蛋白质组学、代谢组学和离子学的生物和技术特征。因此，它将增加调查的敏感性、准确性和解释范围。所开发的统计推断方法和相关开源软件的实用性将在酿酒酵母的功能屏幕上展示，该屏幕整合了不同的转录组、蛋白质组、代谢组和离子数据集。拟议的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有关的案例研究，通过在普渡大学的科学会议和跨学科课程上提供跨学科辅导和短期课程，以及为各系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将在www.stat.Purdue.edu/~ovitek上查阅

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