iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.
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Constraint Based Modeling Going MulticellularJuPOETs: a constrained multiobjective optimization approach to estimate biochemical model ensembles in the Julia programming language.A design-build-test cycle using modeling and experiments reveals interdependencies between upper glycolysis and xylose uptake in recombinant S. cerevisiae and improves predictive capabilities of large-scale kinetic modelsSeeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling.Genome-scale modeling of yeast: chronology, applications and critical perspectives.Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.From correlation to causation: analysis of metabolomics data using systems biology approaches.
P2860
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P2860
iSCHRUNK--In Silico Approach to Characterization and Reduction of Uncertainty in the Kinetic Models of Genome-scale Metabolic Networks.
description
2015 nî lūn-bûn
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2015年の論文
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年学术文章
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2015年學術文章
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2015年學術文章
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2015年學術文章
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name
iSCHRUNK--In Silico Approach t ...... nome-scale Metabolic Networks.
@en
type
label
iSCHRUNK--In Silico Approach t ...... nome-scale Metabolic Networks.
@en
prefLabel
iSCHRUNK--In Silico Approach t ...... nome-scale Metabolic Networks.
@en
P1476
iSCHRUNK--In Silico Approach t ...... nome-scale Metabolic Networks.
@en
P2093
Stefano Andreozzi
P304
P356
10.1016/J.YMBEN.2015.10.002
P577
2015-10-14T00:00:00Z