Parameter uncertainty quantification using surrogate models applied to a spatial model of yeast mating polarization

A common challenge in systems biology is quantifying the effects of unknown parameters and estimating parameter values from data. For many systems, this task is computationally intractable due to expensive model evaluations and large numbers of parameters. In this work, we investigate a new method f...

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Detalles Bibliográficos
Autores principales: Renardy, Marissa, Yi, Tau-Mu, Xiu, Dongbin, Chou, Ching-Shan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993324/
https://www.ncbi.nlm.nih.gov/pubmed/29813055
http://dx.doi.org/10.1371/journal.pcbi.1006181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5993324/
https://www.ncbi.nlm.nih.gov/pubmed/29813055
http://dx.doi.org/10.1371/journal.pcbi.1006181

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