Principled Decision-Making Workflow with Hierarchical Bayesian Models of High-Throughput Dose-Response Measurements

We present a case study applying hierarchical Bayesian estimation on high-throughput protein melting-point data measured across the tree of life. We show that the model is able to impute reasonable melting temperatures even in the face of unreasonably noisy data. Additionally, we demonstrate how to...

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Detalles Bibliográficos
Autores principales: Ma, Eric J., Kummer, Arkadij
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227938/
https://www.ncbi.nlm.nih.gov/pubmed/34201203
http://dx.doi.org/10.3390/e23060727

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8227938/
https://www.ncbi.nlm.nih.gov/pubmed/34201203
http://dx.doi.org/10.3390/e23060727

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