Table 1.
Invited speakers and topics from the Emory Exposome Summer Course.
| Discipline | Speaker | Institution | Title | Topic(s) |
|---|---|---|---|---|
| Environmental health | David Balshaw | National Institute of Environmental Health Sciences (NIEHS) | The Exposome at NIEHS | Emerging concepts and issues in implementing the exposome paradigm |
| Thomas Hartung | Johns Hopkins University | Making Big Sense of Big Data on Little Chemicals | High-throughput toxicity screening; -omics; high-content imaging | |
| Michael Jerrett | University of California, Los Angeles | Sensing the Exposome: Tales from the Tails of Distributions | Key exposome concepts; comprehensive overview of external exposure monitoring | |
| Dean Jones | Emory University | High-Resolution Metabolomics as a Central Platform for Sequencing the Human Exposome | Untargeted metabolomics to monitor the internal exposome | |
| Stephen Rappaport | University of California, Berkeley | The Exposome From Conception to Age 11 | History of the exposome; EWAS strategies | |
| Denis Sarigiannis | Aristotle University of Thessaloniki | The Exposome in Europe | Overview of the Health and Environment-wide Associations Based on Large Population Surveys (HEALS) project | |
| Translational sciences | Christopher Austin | National Center for Advancing Translational Sciences | Some Lessons for the Exposome From Previous “Big Biology” Projects | Recommendations for exposome researchers from other large-scale projects |
| Engineering | Kurt Pennell | Tufts University | Multiplexed Analyte Analysis | Mass spectrometry methods for multiplexed exposure assessment |
| Douglas Walker | Tufts University/Emory University | Chemical Measurement by High-Resolution Metabolomics: Practical Considerations | Key concepts for the application of untargeted metabolomics | |
| Systems biology | Alexandra Maertens | Johns Hopkins University | Making Sense of Metabolomics Data with Networks and Multi-omics Approaches | Overview of network analysis for metabolomics data |
| Nicholas Stroustrup | Harvard University | The C. elegans Lifespan Machine | High-throughput screening to explore the role of the environment in the biology of aging | |
| Eberhard Voit | Georgia Institute of Technology | Assessing the Exposome with Methods of Systems Biology | Mathematical modeling strategies to understand the exposome | |
| Computational toxicology | Allan Peter Davis | North Carolina State University | The Comparative Toxicogenomics Database | Exposure data curation and integration |
| Cecilia Tan | U.S. Environmental Protection Agency (EPA) | Exposome Thinking at the EPA | Exposome concept in risk assessment; high-throughput toxicity screening | |
| John Wambaugh | U.S. Environmental Protection Agency | Playing With Data at EPA: ToxCast, ExpoCast, HTTK, and the Exposome | High-throughput toxicity screening | |
| Bioinformatics | Gari Clifford | Georgia Institute of Technology | Playing in the Cloud with Exposomology (The Raspberry Pi 3 & A PIR Motion Detector) | Demonstration of external exposure sensing with the Raspberry Pi |
| Shuzhao Li | Emory University | Metabolomics Pathway Analysis and Integration | Untargeted metabolomics pathway and network analysis | |
| Chirag Patel | Harvard University | Data Analytics Approaches to Enable EWAS | Overview of EWAS strategies | |
| Nam Pho | Harvard University | Demonstration of Cloud-Based, Data-Driven Exposome Associations with xwas and Rstudio | Demonstration of a cloud-based EWAS analysis | |
| Karan Uppal | Emory University | Bioinformatics Tools for Metabolomics | Untargeted metabolomics data pre-processing and analysis | |
| Computer science | Sri Elaprolu | Amazon Web Services | An Introduction to Amazon Web Services | Overview of cloud computing |
Note: EWAS, exposome-wide association study; HTTK, high-throughput toxicokinetics.