A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast
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What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in YeastNew Insights into Tree Height Distribution Based on Mixed Effects Univariate Diffusion Processes.Single-cell study links metabolism with nutrient signaling and reveals sources of variabilityStochastic models of gene transcription with upstream drives: exact solution and sample path characterization.Correction: a nonlinear mixed effects approach for modeling the cell-to-cell variability of Mig1 dynamics in yeast
P2860
A Nonlinear Mixed Effects Approach for Modeling the Cell-To-Cell Variability of Mig1 Dynamics in Yeast
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2015 nî lūn-bûn
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2015年の論文
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2015年論文
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name
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@ast
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@en
type
label
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@ast
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@en
prefLabel
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@ast
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@en
P2093
P2860
P50
P1433
P1476
A Nonlinear Mixed Effects Appr ...... lity of Mig1 Dynamics in Yeast
@en
P2093
Joachim Almquist
Loubna Bendrioua
Mattias Goksör
P2860
P304
P356
10.1371/JOURNAL.PONE.0124050
P407
P577
2015-04-20T00:00:00Z