This is a continuation proposal that will transition us from the R25T mechanism (that no longer exists) to the T32 mechanism. Our goal in this continuation proposal is to train statistically and computationally oriented individuals (Biostatisticians, Statisticians, Engineers, Computer Scientists, etc.) to function as independent researchers in a multidisciplinary environment focusing on cancer research, researchers who are trained in the fundamentals of Nutrition and Cancer. To achieve this goal we have assembled a team specializing in Biostatistics/Statistics, Bioinformatics, Nutrition and multiple aspects of Cancer. As of January 1, 2016, 26 post- doctoral trainees have completed the program and 1 will be enrolled. We have deliberately reduced the number of trainees due to the uncertainty about continued funding. The Program has the following important aspects. 1) The training is fully multidisciplinary. a) We focus on training statistically and computationally oriented individuals in the biology of Nutrition and Cancer, creating researchers who understand the underlying mechanisms of action in the relationship between Nutrition and Cancer. Such understanding will allow our trainees to contribute at the highest level to the design and analysis of experiments in the area, and to develop fine-tuned statistical methods truly appropriate for the experimental data. b) The statistical and computational methods learned will not typically be from formal courses, but as they arise from experimental data in nutrition laboratories. c) The training will include initial rotations through 3 laboratories; a rotation with the Texas A&M Genomics Facility Quantitative Biology Core, the co-director of which is a diet chemoprevention cancer biologist in our training program; a rotation through the newly created metabolomics facility, the director of which is a mentor in our training program; followed by intensive long-term training in a single laboratory. 2) Each trainee will have at least two mentors. a) A Nutritionist or Cancer research specialist whose research focuses on cancer etiology and prevention. The trainee will be expected to become a full member of the biologist's laboratory, including spending significant time in the laboratory, attending laboratory meetings, consulting for the graduate students and postdoctoral researchers in the laboratory, supervising the analysis of experimental data and eventually posing new problems and approaches. b) A Biostatistician or other computationally oriented individual. Our team includes experts in the analysis of experimental data arising from Nutrition and Cancer, particularly those of a longitudinal nature; the analysis of high throughput expression data; the analysis of proteomics data; the construction and the control of gene regulatory networks, etc. 3) The Principal Investigator (Raymond J. Carroll, Ph.D., a Biostatistician) will continue to devote a significant fraction of his time to the Program. We have also designated a Nutritionist (Nancy Turner, Ph.D.) who will continue to devote a significant fraction of her time in coordinating the Nutrition training. 4) The research mentors focus their efforts on cancer research, and receive their primary research funding from the National Cancer Institute, the National Science Foundation, Department of Defense Breast Cancer Research Program, the National Aeronautics and Space Administration Radiation Biology Program, and the American Institute for Cancer Research. 5) The postdoctoral training is for a minimum of two full years, and in some cases this can be extended to three years. 6) At steady state there will be 4 trainees at any one time, the same number as in the R25T program.
Our goal is to train statistically oriented postdoctoral individuals (Biostatisticians, Statisticians, Engineers, Mathematicians, Computer Scientists, etc.) in the fundamentals of Nutrition and Cancer and to develop them as independent researchers able to function in a multidisciplinary environment focusing on cancer research. To achieve this goal we have assembled a team specializing in Biostatistics/Statistics, Bioinformatics, the biology of Nutrition and Cancer and Toxicology within the Cancer context. Through a combination of laboratory rotations, seminars and research experiences, we expect our trainees to be able to make important contributions in the development of statistical and computational methods that can be targeted to experiments in Nutrition and Cancer, and to function as a true collaborator in teams of biologists.
| Lee, Unkyung; Sun, Yanqing; Scheike, Thomas H et al. (2018) Analysis of Generalized Semiparametric Regression Models for Cumulative Incidence Functions with Missing Covariates. Comput Stat Data Anal 122:59-79 |
| Triff, Karen; McLean, Mathew W; Callaway, Evelyn et al. (2018) Dietary fat and fiber interact to uniquely modify global histone post-translational epigenetic programming in a rat colon cancer progression model. Int J Cancer 143:1402-1415 |
| Bliznyuk, Nikolay; Paciorek, Christopher J; Schwartz, Joel et al. (2014) NONLINEAR PREDICTIVE LATENT PROCESS MODELS FOR INTEGRATING SPATIO-TEMPORAL EXPOSURE DATA FROM MULTIPLE SOURCES. Ann Appl Stat 8:1538-1560 |
