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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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| 出版年: | BMC Bioinformatics |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
BioMed Central
2014
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| 主題: | |
| オンライン･アクセス: | 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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