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Development of a microbial dose response visualization and modelling application for QMRA modelers and educators.
Weir, Mark H; Mitchell, Jade; Flynn, William; Pope, Joanna M.
Afiliación
  • Weir MH; Division of Environmental Health Sciences, College of Public Health, The Ohio State University, 426 Cunz Hall, 1841, Neil Ave, Columbus, OH, 43210, USA.
  • Mitchell J; Department of Civil Environmental and Geodetic Engineering, College of Engineering, The Ohio State University, 2070 Neil Ave., Columbus, OH, 43210, USA.
  • Flynn W; CAMRA Consultants LLC, USA.
  • Pope JM; Department of Biosystems and Agricultural Engineering, College of Engineering, Michigan State University, 524 S. Shaw Lane, East Lansing, MI, 48824, USA.
Environ Model Softw ; 88: 74-83, 2017 Feb.
Article en En | MEDLINE | ID: mdl-29104445
Microbial dose response modelling is vital to a well-characterized microbial risk estimate. Dose response modelling is an inherently multidisciplinary field, which collates knowledge and data from disparate scientific fields. This multidisciplinary nature presents a key challenge to the expansion of microbial dose response modelling into new groups of researchers and modelers. This research employs a dose response optimization R code used in 18 peer-reviewed research studies to develop a multi-functional dose response software. The underlying R code performs an optimization of the two primary dose response models using the MLE method and outputs statistical analyses of the fits and bootstrapped uncertainty information for the models. VizDR (Visual Dose Response) was developed to provide microbial dose response modelling capabilities to a larger audience. VizDR is programmed in JavaScript with underlying Python scripts for intercommunication with Rserve. VizDR allows for dose response model visualization and optimization of a user's own experimental data.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Environ Model Softw Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Environ Model Softw Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos