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Inclusion of high-throughput omics data to describe cellular regulation and genome-wide kinetics is a future trend to further improve the accuracy of the integrative modelling framework for lignocellulosic bioprocess design, optimization and scaling up.
In order to test the effectiveness of our proposed integrative modelling framework, we use a real-world biochemical system, the 'Ras/Raf-1/MEK/ERK' signalling pathway [ 72], which is called 'The RKIP pathway' in this research for ease of description.
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In this research, after introducing two forms of pre-defined component patterns to represent biochemical models, we propose an integrative qualitative and quantitative modelling framework for inferring biochemical systems.
In Sect. 4, we present the integrative quantitative and qualitative modelling framework.
We present a modelling framework that both compares and integrates field-collected dung, visual, and camera trap data to more robustly estimate animal populations in data-scarce environments.
It is the flexibility of the modelling framework that makes it particularly useful for modelling EQ-5D values ([ 10]).
It also provides an extensible modelling framework into which future information could be integrated.
The modelling spread that underlie our results is, moreover, a call for the different global models to further investigate the incorporation of HI in their modelling framework, thereby accounting for possibly interaction effects and feedback linkages.
Note that the modelling framework can only allow differentiation of serotypes for primary infections.
A multi-tissue genome-scale metabolic modelling framework for the analysis of whole plant systems.
Lunn, D. J., Thomas, A., Best, N. & Spiegelhalter, D. WinBUGS — a Bayesian modelling framework: concepts, structure, and extensibility.
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