A Bayesian approach to optimizing cryopreservation protocols

Abstract

Cryopreservation is beset with the challenge of protocol alignment across a wide range of cell types and process variables. By taking a cross-sectional assessment of previously published cryopreservation data (sample means and standard errors) as preliminary meta-data, a decision tree learning analysis (DTLA) was performed to develop an understanding of… (More)
DOI: 10.7717/peerj.1039

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