Title: Development of the Texas A&M Superfund Research Program Computational Platform for Data Integration, Visualization, and Analysis.
Authors: Mukherjee, Rajib; Onel, Melis; Beykal, Burcu; Szafran, Adam T; Stossi, Fabio; Mancini, Michael A; Zhou, Lan; Wright, Fred A; Pistikopoulos, Efstratios N
Published In ESCAPE, (2019)
Abstract: The National Institute of Environmental Health Sciences (NIEHS) Superfund Research Program (SRP) aims to support university-based multidisciplinary research on human health and environmental issues related to hazardous substances and pollutants. The Texas A&M Superfund Research Program comprehensively evaluates the complexities of hazardous chemical mixtures and their potential adverse health impacts due to exposure through a number of multi-disciplinary projects and cores. One of the essential components of the Texas A&M Superfund Research Center is the Data Science Core, which serves as the basis for translating the data produced by the multi-disciplinary research projects into useful knowledge for the community via data collection, quality control, analysis, and model generation. In this work, we demonstrate the Texas A&M Superfund Research Program computational platform, which houses and integrates large-scale, diverse datasets generated across the Center, provides basic visualization service to facilitate interpretation, monitors data quality, and finally implements a variety of state-of-the-art statistical analysis for model/tool development. The platform is aimed to facilitate effective integration and collaboration across the Center and acts as an enabler for the dissemination of comprehensive ad-hoc tools and models developed to address the environmental and health effects of chemical mixture exposure during environmental emergency-related contamination events.
PubMed ID: 31612156
MeSH Terms: No MeSH terms associated with this publication