• Joseph Sturino, Ph.D. Joseph Sturino, Ph.D.
    Joseph Sturino, Ph.D. is currently a Assistant Professor in the Department of Nutrition and Food Science. Dr. Sturino's laboratory uses functional genomics (e.g., comparative genomics, targeted gene knockouts, Biolog phenotype microarrays, and oligonucleotide microarrays) to dissect the role of individual genes in coordinating interaction between gastrointestinal microorganisms (both pathogenic and probiotic) and their human host.
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Purpose of the Program

The programs goal is to train statistically oriented individuals (Biostatisticians, Statisticians, Signal Processors, etc.) to function as independent researchers in a multidisciplinary environment focusing on Nutrition and cancer. To achieve this goal we have assembled a team of researchers specializing in Biostatistics/Statistics, Bioinformatics/Biomedical Imaging and the biology of Nutrition and cancer. Through a combination of didactic coursework, seminars and research experiences, trainees will be expected to make important contributions in the development of statistical methods targeted to experiments in nutrition and cancer, and to function as a true collaborator in teams of biologists, instead of merely as a specialist in setting sample sizes and performing data analysis of simple experiments.
  1. The training will be fully multidisciplinary.
    1. The standard training program in Biostatistics/Statistics focuses typically on advanced training in statistical methods as they are applied to a broad area.
    2. This program focus is entirely different. We focus on training statistically oriented individuals in the biology of Nutrition and cancer, with the idea of creating a cadre of statistically oriented researchers who understand the 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.
    3. The curriculum is carefully tailored to, and completely oriented around, the biology of Nutrition and cancer. For postdoctoral trainees, the statistical methods learned will not be from formal courses, but as they arise from experimental data in nutrition laboratories. We include rotations in genomics, proteomics and microarray facilities.


  2. Each trainee will have three mentors.
    1. A Cancer Biologist whose research focuses on cancer etiology and prevention. The trainee will be expected to become a full member of the nutritionist's laboratory, including attending all laboratory meetings, consulting for all the graduate students and postdoctoral researchers in the laboratory, and supervising the analysis of experimental data.
    2. A Biostatistician/Statistician whose research focuses on the development of statistical methods applicable to experimental data arising from Nutrition and cancer. The trainee will be expected to work with this mentor to develop new statistical methods applicable to experiments arising from the nutritionist's laboratory.
    3. A Bioinformatician/Biomedical Imager whose research focuses on the analysis of DNA microarray data. Because research at Texas A&M University on Nutrition and cancer includes a genetic component, we expect that our trainees will develop an understanding of what microarray data are, and how they are analyzed.

The basic premise is that multidisciplinary teams working on Nutrition and cancer will benefit enormously by inclusion of biologically knowledgeable biostatisticians, and especially biostatisticians who are familiar at a fairly deep level with the biological mechanisms of cancer of most interest to nutritionists. This basic premise is supplemented by our observation that there exist few biostatisticians of the desired type. We intend to train a cadre of individuals so that they are sufficiently knowledgeable in the biological aspects of Nutrition and cancer that they can act as independent researchers in biostatistics focusing on the development of relevant statistical methods, and so that they can act as true collaborators with biologists.