Williams, R.A., Timmis, J. and Qwarnstrom, E.E. (2017) Investigating IKK dynamics in the NF-κB signalling pathway using X-Machines. 2017 IEEE Congress on Evolutionary Computation (CEC). pp. 249-256.
Abstract
The transcription factor NF-κB is a biological component that is central to the regulation of genes involved in the innate immune system. Dysregulation of the pathway is known to be involved in a large number of inflammatory diseases. Although considerable research has been performed since its discovery in 1986, we are still not in a position to control the signalling pathway, and thus limit the effects of NF-κB within promotion of inflammatory diseases. We have developed an agent-based model of the IL-1 stimulated NF-κB signalling pathway, which has been calibrated to wet-lab data at the single-cell level. Through rigorous software engineering, we believe our model provides an abstracted view of the underlying real-world system, and can be used in a predictive capacity through in silico experimentation. In this study, we have focused on the dynamics of the IKK complex and its activation of NF-κB. Our agent-based model suggests that the pathway is sensitive to: variations in the binding probability of IKK to the inhibited NF-κB-IκBα complex; and variations in the temporal rebinding delay of IKK.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IEEE. |
Keywords: | Computational modeling; Biological system modeling; Biomembranes; Proteins; Immune system; Unified modeling language; Data models |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > Department of Infection, Immunity and Cardiovascular Disease |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Jul 2017 09:00 |
Last Modified: | 19 Jul 2017 09:00 |
Published Version: | https://doi.org/10.1109/CEC.2017.7969320 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Refereed: | Yes |
Identification Number: | 10.1109/CEC.2017.7969320 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:119212 |