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BAYESIAN INFERENCE OF STOCHASTIC REACTION NETWORKS USING MULTIFIDELITY SEQUENTIAL TEMPERED MARKOV CHAIN MONTE CARLO
Stochastic reaction network models are often used to explain and predict the dynamics of gene regulation in single cells. These models usually involve several parameters, such as the kinetic rates of chemical reactions, that are not directly measurable and must be inferred from experimental data. Ba...
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| Udgivet i: | Int J Uncertain Quantif |
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| Main Authors: | , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2020
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8127724/ https://ncbi.nlm.nih.gov/pubmed/34007522 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1615/int.j.uncertaintyquantification.2020033241 |
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