Global Gene Expression Profiling of a Population Exposed to a Range of Benzene Levels

Author:

McHale Cliona M.1,Zhang Luoping1,Lan Qing2,Vermeulen Roel3,Li Guilan4,Hubbard Alan E.1,Porter Kristin E.1,Thomas Reuben5,Portier Christopher J.5,Shen Min2,Rappaport Stephen M.1,Yin Songnian4,Smith Martyn T.1,Rothman Nathaniel2

Affiliation:

1. School of Public Health, University of California–Berkeley, Berkeley, California, USA

2. Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA

3. Institute of Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands

4. Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China

5. Environmental Systems Biology Group, Laboratory of Molecular Toxicology, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA

Publisher

Environmental Health Perspectives

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health

Reference48 articles.

1. Improved scoring of functional groups from gene expression data by decorrelating GO graph structure

2. A review of human carcinogens—Part F: Chemical agents and related occupations

3. Significance analysis of functional categories in gene expression studies: a structured permutation approach

4. Bates D Maechler M. 2010. lme4: Linear Mixed-Effects Models Using S4 Classes. R Package Version 0.999375-34 Available: http://cran.r-project.org/web/packages/lme4/index.html accessed 30 September 2010.

5. Controlling the false discovery rate: a practical and powerful approach to multiple testing;Benjamini Y;J R Stat Soc Ser B,1995

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