Purdue University is awarded a grant by the NSF Faculty Early Career Development (CAREER) Program to develop statistical and computational tools for functional proteomics, metabolomics and ionomics. The proposed research will address three inter-related aims: (1) Accurate identifications and quantifications of proteins, metabolites and ions from high-throughput experiments, which generate sparse data in form of mass and nuclear magnetic resonance spectra; (2) Joint interpretation 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 the biological and technological characteristics of proteomics, metabolomics and ionomics. As the result, it will increase the sensitivity, accuracy, and scope of interpretation of the investigations. The utility of the developed methods of statistical inference, and of the associated open-source software, will be demonstrated on functional screens of S. cerevisiae, which integrate heterogeneous transcriptomic, proteomic, metabolomic and ionomic datasets.
The proposed program will contribute to bridging the communication gap between biologists, chemists and statisticians. The project will promote the computational thinking, and the appropriate use of statistical methodology, by making available case studies that are relevant to the user community, by offering interdisciplinary tutorials and short courses at scientific meetings and interdisciplinary courses at Purdue, and by providing mentoring for graduate and undergraduate students across departments. Materials associated with these activities will be available at www.stat.purdue.edu/~ovitek
