Bioinformatics & Systems Biology
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David M. Umbach


Biostatistics & Computational Biology
Institut Pasteur de Bangui
Mauritius

David M. Umbach

Biography

Statistical methods are indispensable tools used by scientists from many disciplines to draw valid inferences from data. Statisticians then have two roles in advancing science: as developers of new and better statistical methods and as shepherds of the appropriate application of statistical tools and of the proper interpretation of their results. Umbach’s research at the NIEHS encompasses both these roles. Much of his work in method’s development has centered on improving study designs and analyses for genetic epidemiology, in particular, on designs that use affected individuals and their parents to understand genetic and environmental contributors to disease risk. A second research interest, related to environmental epidemiology, is developing methods for using measurements on pooled specimens as predictors in regression models that assess relationships between risk factors and disease. He has also contributed to methods in statistical genomics, for example, methods directed at identifying transcription-factor binding sites enriched in ChIP-seq or at assessing aspects of gene expression from RNA-seq data. Recently, he has initiated some work related to toxicological studies of the effects of mixtures of chemical agents.

Research Interest

Biostatistics & Computational Biology

Publications

  • Harmon QE, Umbach DM, Baird DD. Use of Estrogen-Containing Contraception Is Associated With Increased Concentrations of 25-Hydroxy Vitamin D. The Journal of clinical endocrinology and metabolism 2016

  • Lyles RH, Mitchell EM, Weinberg CR, Umbach DM, Schisterman EF. An efficient design strategy for logistic regression using outcome- and covariate-dependent pooling of biospecimens prior to assay. Biometrics 2016 72(3):965-975

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