The Environmental Statistics and Bioinformatics Core will provide cutting edge biostatistical and bioinformatics design and analysis support for all projects. Core faculty are drawn from the Dept. of Biostatistics's Environmental Statistics Program, the HSPH Program of Quantitative Genomics, the HSPH Bioinformatics Core, the Dept. of Epidemiology, and the Dept. of Environmental Health's Program in Environmental Epidemiology. Core faculty have a strong history of collaboration and methods development for applications in environmental health research and genetic epidemiology. Specific areas of expertise include nonparametric smoothing, Bayesian methods, spatial statistics, longitudinal data analysis, environmental risk assessment, statistical genetics, bioinformatics, genome-wide association studies, and genes and environment. Students and postdoctoral fellows in Biostatistics will also provide data analysis support as needed. In addition to handling and overseeing statistical design and analysis for all projects, the core will: ? Advise on data management and ensure that all projects adopt appropriate quality control/quality assurance for data collection, entry, storage and retrieval; ? Provide training in statistical methods and supervise doctoral students working on related research projects; ? Arrange for workshops, seminars and reading groups to ensure that all program faculty and researchers have access to state of the art statistical methods, programs and techniques related to bioinformatics; ? Conduct mission-related statistical research.

Public Health Relevance

The Environmental Statistics and Bioinformatics Core is critical to rigorous study design and analysis of all the projects and ensures the success of the scientific discovery of the Harvard Superfund Center.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Hazardous Substances Basic Research Grants Program (NIEHS) (P42)
Project #
5P42ES016454-03
Application #
8377628
Study Section
Special Emphasis Panel (ZES1-LWJ-M)
Project Start
Project End
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
3
Fiscal Year
2012
Total Cost
$294,555
Indirect Cost
$137,653
Name
Harvard University
Department
Type
DUNS #
149617367
City
Boston
State
MA
Country
United States
Zip Code
02115
Rosa-Parra, Jose A; Tamayo-Ortiz, Marcela; Lamadrid-Figueroa, Hector et al. (2018) Diurnal Cortisol Concentrations and Growth Indexes of 12- to 48-Month-Old Children From Mexico City. J Clin Endocrinol Metab 103:3386-3393
Lee, Jane J; Valeri, Linda; Kapur, Kush et al. (2018) Growth parameters at birth mediate the relationship between prenatal manganese exposure and cognitive test scores among a cohort of 2- to 3-year-old Bangladeshi children. Int J Epidemiol 47:1169-1179
Sun, Ryan; Carroll, Raymond J; Christiani, David C et al. (2018) Testing for gene-environment interaction under exposure misspecification. Biometrics 74:653-662
Sun, Ryan; Wang, Zhaoxi; Claus Henn, Birgit et al. (2018) Identification of novel loci associated with infant cognitive ability. Mol Psychiatry :
Woo, May K; Young, Elisabeth S; Mostofa, Md Golam et al. (2018) Lead in Air in Bangladesh: Exposure in a Rural Community with Elevated Blood Lead Concentrations among Young Children. Int J Environ Res Public Health 15:
Tamayo Y Ortiz, Marcela; Téllez-Rojo, Martha María; Trejo-Valdivia, Belem et al. (2017) Maternal stress modifies the effect of exposure to lead during pregnancy and 24-month old children's neurodevelopment. Environ Int 98:191-197
Lee, Jane J; Kapur, Kush; Rodrigues, Ema G et al. (2017) Anthropometric measures at birth and early childhood are associated with neurodevelopmental outcomes among Bangladeshi children aged 2-3years. Sci Total Environ 607-608:475-482
Maziarz, Marlena; Heagerty, Patrick; Cai, Tianxi et al. (2017) On longitudinal prediction with time-to-event outcome: Comparison of modeling options. Biometrics 73:83-93
Rahman, Mohammad L; Valeri, Linda; Kile, Molly L et al. (2017) Investigating causal relation between prenatal arsenic exposure and birthweight: Are smaller infants more susceptible? Environ Int 108:32-40
Wang, Zhaoxi; Claus Henn, Birgit; Wang, Chaolong et al. (2017) Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment. Environ Health 16:81

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