Scalable and flexible inference framework for stochastic dynamic single-cell models

HIGHLIGHTS

  • who: Sebastian Persson and collaborators from the Department of, University of Gothenburg, Gothenburg, Sweden, Department of Engineering, ETH Zurich, Basel, Switzerland have published the research work: Scalable and flexible inference framework for stochastic dynamic single-cell models, in the Journal: (JOURNAL) of October/22,/2021
  • what: The authors demonstrate the relevance of the approach by studying how cell-to-cell variation in carbon source utilisation affects heterogeneity in the budding yeast Saccharomyces cerevisiae SNF1 nutrient sensing pathway. The authors propose a Bayesian inference framework which enabled the authors to elucidate sources of cell-tocell variability . . .

     

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