Journal article
Dynamics Modeling Signaling Pathway Regulating EGF-Induced Cell Adhesion
IFAC Proceedings Volumes, v 47(3), pp 7486-7491
2014
Abstract
A quantitative modeling approach is developed to dissect the signaling pathways involved in the process of the epidermal growth factor (EGF)-induced dynamic change of cell adhesion. The dynamics model will be constructed based on a system identification process, which is regularly employed in control system design to elucidate the unknown structures and parameters of some of the components in the system based on the prior knowledge and the input/output information of the system. The signaling network that is known to regulate the EGF-induced cell adhesion is designated as the controller which controls the physical process of cell adhesion, i.e. the plant. A nanomechanical sensor in quartz crystal microbalance with dissipation monitoring (QCM-D), which is capable of generating realtime, continuous and measurable signals, will be used for evaluating the system output. The interaction of measurement signal with the cell adhesion complex is modeled as plant. From the model, key structures and parameters of the signaling hierarchy were identified and confirmed. The dynamic pathway output agrees well with the measurement result of energy dissipation from the QCM-D sensor. We expect this proposed study will reveal the decisive reactions of the signaling network that are most critical to regulation of EGF-induced changes in cell adhesion at both normal and disease conditions.
Metrics
10 Record Views
Details
- Title
- Dynamics Modeling Signaling Pathway Regulating EGF-Induced Cell Adhesion
- Creators
- Ruiguo Yang - Michigan State UniversityNing Xi - Michigan State UniversityBo Song - Michigan State UniversityZhiyong Sun - Michigan State UniversityMarcela P. Garcia - Michigan State UniversityLiangliang Chen - Michigan State UniversityJun Xi - Drexel University
- Publication Details
- IFAC Proceedings Volumes, v 47(3), pp 7486-7491
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science; Chemistry
- Scopus ID
- 2-s2.0-84929833480
- Other Identifier
- 991019173462904721