Paper Info
Title
Investigating IKK dynamics in the NF-κB signalling pathway using X-Machines
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.
Year
DOI
Venue
2017
10.1109/CEC.2017.7969320
2017 IEEE Congress on Evolutionary Computation (CEC)
Keywords
Field
DocType
IKK dynamics,IL-1 stimulated NF-κB signalling pathway,X-machines,NF-κB transcription factor,biological component,gene regulation,innate immune system,pathway dysregulation,inflammatory diseases,agent-based model,software engineering,binding probability,temporal rebinding delay
NF-κB,IκB kinase,Gene,Computer science,Artificial intelligence,Immune system,Computational biology,Transcription factor,In silico,Innate immune system,Hedgehog signaling pathway,Bioinformatics,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-5090-4602-7
1
0.35
References 
Authors
8
3
Name
Order
Citations
PageRank
Richard A. Williams171.81
Jonathan Timmis233933.03
Eva E Qwarnstrom331.41