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Publication Detail

Title: Informatics and Data Analytics to Support Exposome-Based Discovery for Public Health.

Authors: Manrai, Arjun K; Cui, Yuxia; Bushel, Pierre R; Hall, Molly; Karakitsios, Spyros; Mattingly, Carolyn J; Ritchie, Marylyn; Schmitt, Charles; Sarigiannis, Denis A; Thomas, Duncan C; Wishart, David; Balshaw, David M; Patel, Chirag J

Published In Annu Rev Public Health, (2017 Mar 20)

Abstract: The complexity of the human exposome-the totality of environmental exposures encountered from birth to death-motivates systematic, high-throughput approaches to discover new environmental determinants of disease. In this review, we describe the state of science in analyzing the human exposome and provide recommendations for the public health community to consider in dealing with analytic challenges of exposome-based biomedical research. We describe extant and novel analytic methods needed to associate the exposome with critical health outcomes and contextualize the data-centered challenges by drawing parallels to other research endeavors such as human genomics research. We discuss efforts for training scientists who can bridge public health, genomics, and biomedicine in informatics and statistics. If an exposome data ecosystem is brought to fruition, it will likely play a role as central as genomic science has had in molding the current and new generations of biomedical researchers, computational scientists, and public health research programs.

PubMed ID: 28068484 Exiting the NIEHS site

MeSH Terms: Biomedical Research*; Computational Biology*; Ecosystem; Environmental Exposure/adverse effects*; Humans; Public Health*; Risk Factors

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