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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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Detalhes bibliográficos
Publicado no:Int J Uncertain Quantif
Main Authors: Catanach, Thomas A., Vo, Huy D., Munsky, Brian
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
Assuntos:
Acesso em linha: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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