iSCHRUNK – I n S ilico Approach to Ch aracterization and R eduction of Un certainty in the K inetic Models of Genome-scale Metabolic Networks

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Title
iSCHRUNK – I n S ilico Approach to Ch aracterization and R eduction of Un certainty in the K inetic Models of Genome-scale Metabolic Networks
Authors
Keywords
Large-scale kinetic models, Kinetic parameters, Enzyme saturations, Uncertainty reduction, Monte Carlo sampling, Machine learning
Journal
METABOLIC ENGINEERING
Volume 33, Issue -, Pages 158-168
Publisher
Elsevier BV
Online
2015-10-25
DOI
10.1016/j.ymben.2015.10.002

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