| 1 |
Data-driven reverse engineering of signaling pathways using ensembles of dynamic models
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| 2 |
Metabolic engineering with multi-objective optimization of kinetic models
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| 3 |
PREMER: Parallel reverse engineering of biological networks with information theory
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| 4 |
Identifiability of large nonlinear biochemical networks
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| 5 |
Structural identifiability of dynamic systems biology models
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| 6 |
On the relationship between sloppiness and identifiability
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| 7 |
BioPreDyn-bench: A suite of benchmark problems for dynamic modelling in systems biology
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| 8 |
A consensus approach for estimating the predictive accuracy of dynamic models in biology
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| 9 |
Enabling network inference methods to handle missing data and outliers
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| 10 |
MIDER: Network inference with mutual information distance and entropy reduction
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| 11 |
Reverse engineering and identification in systems biology: Strategies, perspectives and challenges
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| 12 |
High-confidence predictions in systems biology dynamic models
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| 13 |
Adaptive tracking in mobile robots with input-output linearization
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| 14 |
MEIGO: An open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics
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| 15 |
A cooperative strategy for parameter estimation in large scale systems biology models
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| 16 |
Passive internet-based crane teleoperation with haptic aids
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| 17 |
Multi-criteria optimization of regulation in metabolic networks
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| 18 |
Damping injection by reset control
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| 19 |
Global optimization in systems biology: Stochastic methods and their applications
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| 20 |
Use of a generalized Fisher equation for global optimization in chemical kinetics
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