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A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks
We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introduci...
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| 出版年: | PLoS One |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Public Library of Science
2017
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5552360/ https://ncbi.nlm.nih.gov/pubmed/28797087 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0182015 |
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