The Bioinformatics Core aims to provide statistical expertise and programming support via a transdisciplinary approach during the implementation of projects 1 to 4, as well as during TREC pilot studies.
The specific aims are: 1). To provide statistical and methodological support to the Harvard TREC Center, and develop new methods of answering research questions raised by the Center;2). To interface epidemiology, basic sciences, and clinical medicine, and ensure that sound statistical methods are incorporated into all research and training activities at the TREC Center;3). To manage and maintain large data sets appropriate for use in secondary epidemiologic analyses regarding obesity and energetic issues, and for developing and refining measures of obesity and cancer-related phenotypes;and 4). To ensure timely sharing of data and their submission for centralized data collection at the Coordinating Center. Under the leadership of Dr. Bernard Rosner, Core members will meet monthly to review statistical and measurement issues across the projects. Members will participate in the annual retreat with presentations on state-of-the-art statistical methodology systems and multilevel analysis. Individual statisticians will meet regularly with the research teams they support and with the lead investigators of each developmental project. The Bioinformatics team has worked closely with all Project Leaders in developing the statistical methods and power calculations described in the proposals. The Core will actively participate in transdisciplinary research as an integral part ofthe TREC Center and will develop new methods (or apply existing methods in novel ways across projects), with a particular focus of working with pilot study recipients and new investigators.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Specialized Center--Cooperative Agreements (U54)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-SRLB-4)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Harvard University
United States
Zip Code
Malik, Vasanti S; Li, Yanping; Tobias, Deirdre K et al. (2016) Dietary Protein Intake and Risk of Type 2 Diabetes in US Men and Women. Am J Epidemiol 183:715-28
Hruby, Adela; Manson, JoAnn E; Qi, Lu et al. (2016) Determinants and Consequences of Obesity. Am J Public Health 106:1656-62
Global BMI Mortality Collaboration (2016) Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet 388:776-86
Cespedes, Elizabeth M; Bhupathiraju, Shilpa N; Li, Yanping et al. (2016) Long-term changes in sleep duration, energy balance and risk of type 2 diabetes. Diabetologia 59:101-9
James, Peter; Jankowska, Marta; Marx, Christine et al. (2016) ""Spatial Energetics"": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity. Am J Prev Med 51:792-800
Schmitz, Kathryn H; Gehlert, Sarah; Patterson, Ruth E et al. (2016) TREC to WHERE? Transdisciplinary Research on Energetics and Cancer. Clin Cancer Res 22:1565-71
Song, Mingyang; Hu, Frank B; Spiegelman, Donna et al. (2016) Long-term status and change of body fat distribution, and risk of colorectal cancer: a prospective cohort study. Int J Epidemiol 45:871-83
Birmann, Brenda M; Barnard, Mollie E; Bertrand, Kimberly A et al. (2016) Nurses' Health Study Contributions on the Epidemiology of Less Common Cancers: Endometrial, Ovarian, Pancreatic, and Hematologic. Am J Public Health 106:1608-15
Song, Mingyang; Mehta, Raaj S; Wu, Kana et al. (2016) Plasma Inflammatory Markers and Risk of Advanced Colorectal Adenoma in Women. Cancer Prev Res (Phila) 9:27-34
Huang, Ru-Yi; Huang, Chuan-Chin; Hu, Frank B et al. (2016) Vegetarian Diets and Weight Reduction: a Meta-Analysis of Randomized Controlled Trials. J Gen Intern Med 31:109-16

Showing the most recent 10 out of 114 publications