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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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Vydáno v:BMC Bioinformatics
Hlavní autoři: Wu, Qianqian, Smith-Miles, Kate, Tian, Tianhai
Médium: Artigo
Jazyk:Inglês
Vydáno: BioMed Central 2014
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC4243104/
https://ncbi.nlm.nih.gov/pubmed/25473744
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-15-S12-S3
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