(371p) Time-Varying Model Identification of Nonlinear Systems with Partially Known Model Structure: Application to NF?B Signaling Pathway Induced by LPS and BFA
AIChE Annual Meeting
2019
2019 AIChE Annual Meeting
Computing and Systems Technology Division
Interactive Session: Systems and Process Control
Tuesday, November 12, 2019 - 3:30pm to 5:00pm
The validity of the proposed method was demonstrated by developing a time-varying model for the NFκB signaling pathway induced by brefeldin A (BFA). Although the NFκB system has been extensively studied because of its importance in cellular survival and inflammation, it is not yet fully characterized. This is partially because the NFκB signaling pathway can be activated by around 100 different stimuli with different corresponding reaction mechanisms, and the NFκB signaling pathway initiated by only a few stimuli such as LPS is well characterized. Compared to LPS, the NFκB dynamics induced by BFA are only partially understood with the limited model availability. Based on the fact that the NFκB signaling dynamics induced by both LPS and BFA share core mechanisms, the proposed mechanism was implemented to construct a time-varying model for the BFA-induced NFκB signaling pathway based on the model for the LPS-induced dynamics and flow cytometry measurements [5]. Compared to the time-invariant model developed in the previous study [5], the proposed model was able to predict the signaling dynamics more accurately, which demonstrated the validity of the proposed methodology. In summary, the proposed methodology can reduce the overall time required for the model development without compromising the prediction accuracy when the underlying chemical reaction network is only partially known.
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