T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

Nick D. L. Owens; Andy Greensted; Jon Timmis; Andy Tyrrell

T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

Nick D. L. Owens, Andy Greensted, Jon Timmis, Andy Tyrrell

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The T cell is able to perform line-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.

Original language	English
Title of host publication	ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS
Editors	PS Andrews, J Timmis, NDL Owens, U Aickelin, E Hart, A Hone, AM Tyrrell
Place of Publication	BERLIN
Publisher	Springer
Pages	122-135
Number of pages	14
Volume	5666 LNCS
ISBN (Print)	978-3-642-03245-5
Publication status	Published - 2009
Event	8th International Conference on Artificial Immune Systems - York Duration: 9 Aug 2009 → 12 Aug 2009

Conference

Conference	8th International Conference on Artificial Immune Systems
City	York
Period	9/08/09 → 12/08/09

Cite this

@inproceedings{0044a0b788ec48fca02b1abfc2afa877,

title = "T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection",

abstract = "The T cell is able to perform line-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.",

author = "Owens, {Nick D. L.} and Andy Greensted and Jon Timmis and Andy Tyrrell",

year = "2009",

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editor = "PS Andrews and J Timmis and NDL Owens and U Aickelin and E Hart and A Hone and AM Tyrrell",

booktitle = "ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS",

publisher = "Springer",

address = "Germany",

note = "8th International Conference on Artificial Immune Systems ; Conference date: 09-08-2009 Through 12-08-2009",

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Owens, NDL, Greensted, A, Timmis, J & Tyrrell, A 2009, T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection. in PS Andrews, J Timmis, NDL Owens, U Aickelin, E Hart, A Hone & AM Tyrrell (eds), ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS. vol. 5666 LNCS, Springer, BERLIN, pp. 122-135, 8th International Conference on Artificial Immune Systems, York, 9/08/09.

T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection. / Owens, Nick D. L.; Greensted, Andy; Timmis, Jon et al.

ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS. ed. / PS Andrews; J Timmis; NDL Owens; U Aickelin; E Hart; A Hone; AM Tyrrell. Vol. 5666 LNCS BERLIN : Springer, 2009. p. 122-135.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

AU - Owens, Nick D. L.

AU - Greensted, Andy

AU - Timmis, Jon

AU - Tyrrell, Andy

PY - 2009

Y1 - 2009

N2 - The T cell is able to perform line-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.

AB - The T cell is able to perform line-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.

UR - http://www.scopus.com/inward/record.url?scp=70350337144&partnerID=8YFLogxK

M3 - Conference contribution

SN - 978-3-642-03245-5

VL - 5666 LNCS

SP - 122

EP - 135

BT - ARTIFICIAL IMMUNE SYSTEMS, PROCEEDINGS

A2 - Andrews, PS

A2 - Timmis, J

A2 - Owens, NDL

A2 - Aickelin, U

A2 - Hart, E

A2 - Hone, A

A2 - Tyrrell, AM

PB - Springer

CY - BERLIN

T2 - 8th International Conference on Artificial Immune Systems

Y2 - 9 August 2009 through 12 August 2009

ER -

T Cell Receptor Signalling Inspired Kernel Density Estimation and Anomaly Detection

Abstract

Conference

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