Bioinformatics & Systems Biology

Bioinformatics & Systems Biology Experts

Clarice R. Weinberg

Biostatistics & Computational Biology
Institut Pasteur de Bangui

Clarice R. Weinberg


Clarice Weinberg, Ph.D., is Acting Branch Chief and a principal investigator in the Biostatistics and Computational Biology Branch. She holds a secondary appointment in the NIEHS Epidemiology Branch, and adjunct professorships at the University of North Carolina at Chapel Hill in both Epidemiology and Biostatistics. Epidemiology is one of the best tools for studying human health effects of environmental exposures. However, this tool is inherently imperfect and prone to imprecision and biases. Weinberg's research has focused on the development of improved methods for design and analysis that account for sources of bias, missing data, response heterogeneity and mismeasurement in epidemiologic studies. Methodologic research is most fruitful when it arises in the context of real applications to epidemiology. Her extensive collaborations with epidemiologists at NIEHS have inspired nearly all of this work. She is also developing improved designs and methods of analysis to elucidate joint etiologic roles of multiple genetic variants and environmental susceptibility factors. Complex diseases, such as birth defects, heart diseases, neurodegenerative disease and cancer, are caused by time and the combined action of genetic susceptibility factors and exposures. Of particular interest is the interplay between genetic factors, both maternal and fetal, and maternal exposures in influencing fetal survival, embryologic development and postnatal long-term health. Methods being developed in this area will be applied to data from an international study of oral clefting, to a family-based study of young-onset breast cancer and to a study of osteosarcoma, a bone cancer that occurs in childhood.

Research Interest

Biostatistics & Computational Biology


  • Rockhill, B., Newman, B., and Weinberg, C.R. Use and misuse of population attributable fractions. American Journal of Public Health, 88(1): 15-19, 1998.

  • Umbach DM, Weinberg CR. Designing and analyzing case-control studies to exploit independence of genotype and exposure. Statistics in Medicine 1997; 16:1731-1743.

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