This application is for continuation of a training program in biostatistics with a specific focus on cancer research. The training program supports six students each year. The practice of biostatistics is changing, especially in the area of cancer research. Discoveries over the last two decades into the molecular, biochemical, and genetic components of cell growth and development lave changed our understanding of what makes a normal cell become cancerous and then metastasize. Multidisciplinary research teams are at the heart of modern approaches to fighting cancer, and biostatisticians more and more are a part of such teams. Such teamwork requires that the statistician be conversant with molecular biologists, pathologists, and, of course, clinical oncologists if the group of co-investigators is to succeed. Effective biostatistical collaboration thus requires broad training in statistics, probability, computational methods, as well as cancer biology and medical ethics. The Department of Statistics, Rice University, and departments in the Division of Quantitative Sciences at the University of Texas M. D. Anderson Cancer Center (UTMDACC) have joined forces with their collaborators in the clinical and basic sciences to develop a unique training program that combines their respective strengths to train biostatisticians in cancer research. The goal of this Training Program in Biostatistics is to prepare a new generation of biostatisticians who will work side-by-side with biomedical investigators in modern cancer research. Our program aims to provide trainees with Rigorous training in statistics and probability;Practical experience in basic and clinical cancer research;and Training in biological aspects of cancer and medical research ethics. Students in this program follow the standard course of study expected of Ph.D. students in the Department of Statistics at Rice, with additional coursework in biostatistics, biology, and ethics, as well as special seminars and workshops at both institutions. With faculty expertise in Bayesian methods, decision theory, cancer clinical trials, cancer screening, survival analysis, statistical genetics, genomics, bioinformatics, and statistical computing, trainees will receive a broad background in biostatistics necessary for modern cancer research. Summer internships and laboratory rotations provide practical experience in the student's training. Relevance: Combining the educational resources available at Rice University and UTMDACC with practical experience will enable trainees upon completion to make fundamental contributions to cancer research working alongside biomedical investigators. Such close collaboration will lead to more efficient study designs and data analysis, allowing translation of therapeutic theories to clinical application more quickly.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Institutional National Research Service Award (T32)
Project #
5T32CA096520-08
Application #
8312338
Study Section
Subcommittee G - Education (NCI)
Program Officer
Lim, Susan E
Project Start
2002-07-01
Project End
2013-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
8
Fiscal Year
2012
Total Cost
$246,509
Indirect Cost
$12,975
Name
Rice University
Department
Biostatistics & Other Math Sci
Type
Schools of Engineering
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005
Chiang, Sharon; Levin, Harvey S; Wilde, Elisabeth et al. (2016) White matter structural connectivity changes correlate with epilepsy duration in temporal lobe epilepsy. Epilepsy Res 120:37-46
Chiang, Sharon; Cassese, Alberto; Guindani, Michele et al. (2016) Time-dependence of graph theory metrics in functional connectivity analysis. Neuroimage 125:601-15
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Peterson, Christine B; Stingo, Francesco C; Vannucci, Marina (2016) Joint Bayesian variable and graph selection for regression models with network-structured predictors. Stat Med 35:1017-31
Snowdon, Kyle A; Smeak, Daniel D; Chiang, Sharon (2016) Risk Factors for Dehiscence of Stapled Functional End-to-End Intestinal Anastomoses in Dogs: 53 Cases (2001-2012). Vet Surg 45:91-9
Peterson, Christine B; Stingo, Francesco C; Vannucci, Marina (2015) Bayesian Inference of Multiple Gaussian Graphical Models. J Am Stat Assoc 110:159-174
Youmans, Bonnie P; Ajami, Nadim J; Jiang, Zhi-Dong et al. (2015) Characterization of the human gut microbiome during travelers' diarrhea. Gut Microbes 6:110-9
Chiang, Sharon; Levin, Harvey S; Haneef, Zulfi (2015) Computer-automated focus lateralization of temporal lobe epilepsy using fMRI. J Magn Reson Imaging 41:1689-94
Chiang, Sharon; Stern, John M; Engel Jr, Jerome et al. (2015) Structural-functional coupling changes in temporal lobe epilepsy. Brain Res 1616:45-57

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