The Biostatistics Core is designed to enhance the UNC Superfund Research Program's assessment and reduction of risks to human health associated with Superfund high priority chemicals. The five projects in the SRP present considerable biostatistical issues and bioinformatics challenges that are central to the success of the projects. Our overall aims are to (i) provide state-of-the-art biostatistics and bioinformatics expertise, end-user analytical support, and tool development;(ii) to develop new methods and tools as necessary to address project objectives;(iii) to foster a unique training environment for students, postdoctoral fellows, and faculty to prepare them for the new and complex challenges presented by modern datasets. The Core faculty and staff have a range of complementary skills, which will lead to a unified approaches to data interpretation, integration and cross-platform analysis. Collectively, the Core is highly relevant to the Superfund Program, as it will: ? support interdisciplinary (toxicology, genetics, biostatistics, pharmacokinetic modeling) research to elucidate the genetic basis of dose-response and susceptibility; ? develop and use state-of-the-art statistical techniques and analysis tools for systems biology approaches; ? identify potential biomarkers linked to genetic differences in toxicant metabolism and/or response;and ? generate knowledge that is directly applicable to quantitative elucidation of risk. The Core will be involved at the earliest stages of each project, assisting investigators in each step of planning and executing the projects. Each Core faculty member is assigned a role to two projects. A staff statistician with considerable bioinformatics experience will serve as a dedicated analyst, under the guidance of Core faculty members. The Core director will report to the SRP Director, and members, who already collaborate extensively, will meet regularly with the investigators and with each other to plan and exchange ideas.
The overall Program is highly relevant to public health, providing improved understanding of risk sources and risk variation due to exposure to hazardous chemicals. The Biostatistics Core will enhance this relevance, maximizing the information gained from each project and enabling the use of modern bioinformatics approaches to complex datasets.
|Balik-Meisner, Michele; Truong, Lisa; Scholl, Elizabeth H et al. (2018) Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure. Environ Health Perspect 126:067010|
|To, Kimberly T; Fry, Rebecca C; Reif, David M (2018) Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi. BioData Min 11:10|
|Dalaijamts, Chimeddulam; Cichocki, Joseph A; Luo, Yu-Syuan et al. (2018) Incorporation of the glutathione conjugation pathway in an updated physiologically-based pharmacokinetic model for perchloroethylene in mice. Toxicol Appl Pharmacol 352:142-152|
|Gray, Kathleen M (2018) From Content Knowledge to Community Change: A Review of Representations of Environmental Health Literacy. Int J Environ Res Public Health 15:|
|Li, Gen; Jima, Dereje; Wright, Fred A et al. (2018) HT-eQTL: integrative expression quantitative trait loci analysis in a large number of human tissues. BMC Bioinformatics 19:95|
|Adebambo, Oluwadamilare A; Shea, Damian; Fry, Rebecca C (2018) Cadmium disrupts signaling of the hypoxia-inducible (HIF) and transforming growth factor (TGF-?) pathways in placental JEG-3 trophoblast cells via reactive oxygen species. Toxicol Appl Pharmacol 342:108-115|
|Smeester, Lisa; Fry, Rebecca C (2018) Long-Term Health Effects and Underlying Biological Mechanisms of Developmental Exposure to Arsenic. Curr Environ Health Rep 5:134-144|
|Luo, Yu-Syuan; Furuya, Shinji; Chiu, Weihsueh et al. (2018) Characterization of inter-tissue and inter-strain variability of TCE glutathione conjugation metabolites DCVG, DCVC, and NAcDCVC in the mouse. J Toxicol Environ Health A 81:37-52|
|Singleton, David R; Lee, Janice; Dickey, Allison N et al. (2018) Polyphasic characterization of four soil-derived phenanthrene-degrading Acidovorax strains and proposal of Acidovorax carolinensis sp. nov. Syst Appl Microbiol 41:460-472|
|Luo, Yu-Syuan; Hsieh, Nan-Hung; Soldatow, Valerie Y et al. (2018) Comparative analysis of metabolism of trichloroethylene and tetrachloroethylene among mouse tissues and strains. Toxicology 409:33-43|
Showing the most recent 10 out of 505 publications