T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

  • Nick D. L. Owens
  • Andy Greensted
  • Jon Timmis
  • Andy Tyrrell
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5666)


The T cell is able to perform fine-grained anomaly detection via its T Cell Receptor and intracellular signalling networks. We abstract from models of T Cell signalling to develop a new Artificial Immune System concepts involving the internal components of the TCR. We show that the concepts of receptor signalling have a natural interpretation as Parzen Window Kernel Density Estimation applied to anomaly detection. We then demonstrate how the dynamic nature of the receptors allows anomaly detection when probability distributions vary in time.


Negative Feedback Anomaly Detection Kernel Density Estimation Single Receptor Receptor Position 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Nick D. L. Owens
    • 1
  • Andy Greensted
    • 1
  • Jon Timmis
    • 1
    • 2
  • Andy Tyrrell
    • 1
  1. 1.Department of ElectronicsUniversity of YorkYorkUK
  2. 2.Department of Computer ScienceUniversity of YorkYorkUK

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