Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy

Scheidegger, Stephan; Mingo Barba, Sergio; Fellermann, Harold; Gaipl, Udo S.

doi:10.1007/978-3-031-23929-8_19

Publication type:	Conference paper
Type of review:	Peer review (publication)
Title:	Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy
Authors:	Scheidegger, Stephan Mingo Barba, Sergio Fellermann, Harold Gaipl, Udo S.
et. al:	No
DOI:	10.1007/978-3-031-23929-8_19
Proceedings:	Artificial Life and Evolutionary Computation
Editors of the parent work:	Schneider, Johannes J. Weyland, Mathias S. Flumini, Dandolo Füchslin, Rudolf M.
Page(s):	195
Pages to:	206
Conference details:	XV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021
Issue Date:	2022
Series:	Communications in Computer and Information Science
Series volume:	1722
Publisher / Ed. Institution:	Springer
Publisher / Ed. Institution:	Cham
ISBN:	978-3-031-23928-1 978-3-031-23929-8
Language:	English
Subjects:	Immune system; Tumour ecosystem; Systems medicine; Perceptron; Antigen pattern; Anti-cancer therapy; Adaptive immune response
Subject (DDC):	616: Internal medicine and diseases
Abstract:	Artificial immune-tumor ecosystems can serve as models to explore the complex tumor-host-immune – interactions in silico. This may contribute to a better understanding of the conditions leading to anti-cancer immune response in patients during anti-cancer therapy. For model development, it is important to identify an appropriate model structure which is suitable to mimic the behavior of real biological systems. In this study, the influence of the number of antigens in an artificial adaptive immune system onto an immune-tumor ecosystem during and after radiation therapy (RT) is investigated. For antigen pattern recognition, a perceptron is used. The simulated scenarios with 4, 9 and 12 antigens exhibit differences in the immune response, but in all cases, perceptron weights for host tissue evolve after RT into negative values, leading to an immune-suppressive effect. This effect results from the evolution of the populations in the ecosystem and the training of the perceptron. In conclusion, the response of the proposed artificial immune system is strongly dependent on the ecosystem dynamics, which seems to be the case for the real biological systems as well.
URI:	https://digitalcollection.zhaw.ch/handle/11475/27070
Fulltext version:	Published version
License (according to publishing contract):	Licence according to publishing contract
Departement:	School of Engineering
Organisational Unit:	Institute of Applied Mathematics and Physics (IAMP)
Published as part of the ZHAW project:	Hyperboost
Appears in collections:	Publikationen School of Engineering

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Scheidegger, S., Mingo Barba, S., Fellermann, H., & Gaipl, U. S. (2022). Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy [Conference paper]. In J. J. Schneider, M. S. Weyland, D. Flumini, & R. M. Füchslin (Eds.), Artificial Life and Evolutionary Computation (pp. 195–206). Springer. https://doi.org/10.1007/978-3-031-23929-8_19

Scheidegger, S. et al. (2022) ‘Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy’, in J.J. Schneider et al. (eds) Artificial Life and Evolutionary Computation. Cham: Springer, pp. 195–206. Available at: https://doi.org/10.1007/978-3-031-23929-8_19.

S. Scheidegger, S. Mingo Barba, H. Fellermann, and U. S. Gaipl, “Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy,” in Artificial Life and Evolutionary Computation, 2022, pp. 195–206. doi: 10.1007/978-3-031-23929-8_19.

SCHEIDEGGER, Stephan, Sergio MINGO BARBA, Harold FELLERMANN und Udo S. GAIPL, 2022. Influence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapy. In: Johannes J. SCHNEIDER, Mathias S. WEYLAND, Dandolo FLUMINI und Rudolf M. FÜCHSLIN (Hrsg.), Artificial Life and Evolutionary Computation. Conference paper. Cham: Springer. 2022. S. 195–206. ISBN 978-3-031-23928-1

Scheidegger, Stephan, Sergio Mingo Barba, Harold Fellermann, and Udo S. Gaipl. 2022. “Influence of the Antigen Pattern Vector on the Dynamics in a Perceptron-Based Artificial Immune - Tumour- Ecosystem during and after Radiation Therapy.” Conference paper. In Artificial Life and Evolutionary Computation, edited by Johannes J. Schneider, Mathias S. Weyland, Dandolo Flumini, and Rudolf M. Füchslin, 195–206. Cham: Springer. https://doi.org/10.1007/978-3-031-23929-8_19.

Scheidegger, Stephan, et al. “Influence of the Antigen Pattern Vector on the Dynamics in a Perceptron-Based Artificial Immune - Tumour- Ecosystem during and after Radiation Therapy.” Artificial Life and Evolutionary Computation, edited by Johannes J. Schneider et al., Springer, 2022, pp. 195–206, https://doi.org/10.1007/978-3-031-23929-8_19.