Approximate Bayesian computation schemes for parameter inference of discrete stochastic models using simulated likelihood density

BACKGROUND: Mathematical modeling is an important tool in systems biology to study the dynamic property of complex biological systems. However, one of the major challenges in systems biology is how to infer unknown parameters in mathematical models based on the experimental data sets, in particular,...

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Detalles Bibliográficos
Autores principales: Wu, Qianqian, Smith-Miles, Kate, Tian, Tianhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4243104/
https://www.ncbi.nlm.nih.gov/pubmed/25473744
http://dx.doi.org/10.1186/1471-2105-15-S12-S3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4243104/
https://www.ncbi.nlm.nih.gov/pubmed/25473744
http://dx.doi.org/10.1186/1471-2105-15-S12-S3

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