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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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| Publicado no: | BMC Bioinformatics |
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| Main Authors: | , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
BioMed Central
2014
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| Assuntos: | |
| Acesso em linha: | 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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