CORE C: The staff of the Biostatistics Core will be responsible for providing biostatistical support to the research of this program. The Biostatistical Core is under the supervision of Dr. Timothy D. Johnson of the Biostatistics Department in the University of Michigan School of Public Health. The core provides assistance in the design, analysis and interpretation of preclinical and animal experiments of the program. Core personnel will interact with project investigators to ensure that appropriate designs and methods of analysis are used. Design issues involve selection of dose, randomization, timing of measurements and sample size considerations. For data analyses, the core will ensure that efficient methods are used. Standard graphical, group comparison and correlation methods of analysis will be used for initial investigation of the experimental data. Mixed model methods will be used for efficient use of the data in experiments involving repeated measures. Dr. Johnson is experienced in the design and analysis of both animal and clinical data. This will ensure that all data obtained from all Projects will be collected efficiently and analyzed appropriately. Public Health: Overall, this research effort will develop drug paradigms and treatment combinations for target stem cell populations in animal models. These pre-clinical experiments have the potential for translation to clinical trials.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Specialized Center (P50)
Project #
5P50CA093990-11
Application #
8382076
Study Section
Special Emphasis Panel (ZCA1-SRRB-9)
Project Start
Project End
2014-08-31
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
11
Fiscal Year
2012
Total Cost
$51,438
Indirect Cost
$18,144
Name
University of Michigan Ann Arbor
Department
Type
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Keith, Lauren; Ross, Brian D; Galbán, Craig J et al. (2016) Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping. Tomography 2:267-275
Nyati, Shyam; Chator, Areeb; Schinske, Katerina et al. (2016) A Requirement for ZAK Kinase Activity in Canonical TGF-? Signaling. Transl Oncol 9:473-481
Stacer, A C; Fenner, J; Cavnar, S P et al. (2016) Endothelial CXCR7 regulates breast cancer metastasis. Oncogene 35:1716-24
Al-Dujaili, Saja A; Koh, Amy J; Dang, Ming et al. (2016) Calcium Sensing Receptor Function Supports Osteoblast Survival and Acts as a Co-Factor in PTH Anabolic Actions in Bone. J Cell Biochem 117:1556-67
Joshi, Bishnu P; Pant, Asha; Duan, Xiyu et al. (2016) Multimodal Video Colonoscope for Targeted Wide-Field Detection of Nonpolypoid Colorectal Neoplasia. Gastroenterology 150:1084-1086
Baer, A H; Hoff, B A; Srinivasan, A et al. (2015) Feasibility analysis of the parametric response map as an early predictor of treatment efficacy in head and neck cancer. AJNR Am J Neuroradiol 36:757-62
Boes, Jennifer L; Bule, Maria; Hoff, Benjamin A et al. (2015) The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans. Tomography 1:69-77
Luker, K E; Pata, P; Shemiakina, I I et al. (2015) Comparative study reveals better far-red fluorescent protein for whole body imaging. Sci Rep 5:10332
Chang, S Laura; Cavnar, Stephen P; Takayama, Shuichi et al. (2015) Cell, isoform, and environment factors shape gradients and modulate chemotaxis. PLoS One 10:e0123450
Wang, Lizhong; Liu, Runhua; Ye, Peiying et al. (2015) Intracellular CD24 disrupts the ARF-NPM interaction and enables mutational and viral oncogene-mediated p53 inactivation. Nat Commun 6:5909

Showing the most recent 10 out of 161 publications