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dc.contributor.authorScheidegger, Stephan-
dc.contributor.authorMingo Barba, Sergio-
dc.contributor.authorFellermann, Harold-
dc.contributor.authorGaipl, Udo S.-
dc.date.accessioned2023-02-17T10:18:21Z-
dc.date.available2023-02-17T10:18:21Z-
dc.date.issued2022-
dc.identifier.isbn978-3-031-23928-1de_CH
dc.identifier.isbn978-3-031-23929-8de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/27070-
dc.description.abstractArtificial 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.de_CH
dc.language.isoende_CH
dc.publisherSpringerde_CH
dc.relation.ispartofseriesCommunications in Computer and Information Sciencede_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectImmune systemde_CH
dc.subjectTumour ecosystemde_CH
dc.subjectSystems medicinede_CH
dc.subjectPerceptronde_CH
dc.subjectAntigen patternde_CH
dc.subjectAnti-cancer therapyde_CH
dc.subjectAdaptive immune responsede_CH
dc.subject.ddc616: Innere Medizin und Krankheitende_CH
dc.titleInfluence of the antigen pattern vector on the dynamics in a perceptron-based artificial immune - tumour- ecosystem during and after radiation therapyde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Angewandte Mathematik und Physik (IAMP)de_CH
zhaw.publisher.placeChamde_CH
dc.identifier.doi10.1007/978-3-031-23929-8_19de_CH
zhaw.conference.detailsXV International Workshop on Artificial Life and Evolutionary Computation (WIVACE), Winterthur, Switzerland, 15-17 September 2021de_CH
zhaw.funding.euinfo:eu-repo/grantAgreement/EC/H2020/955625//Creation of advanced cancer treatment planning to boost the effect of Radiotherapy by combining with hyperthermia, heating the tumor/HYPERBOOSTde_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end206de_CH
zhaw.pages.start195de_CH
zhaw.parentwork.editorSchneider, Johannes J.-
zhaw.parentwork.editorWeyland, Mathias S.-
zhaw.parentwork.editorFlumini, Dandolo-
zhaw.parentwork.editorFüchslin, Rudolf M.-
zhaw.publication.statuspublishedVersionde_CH
zhaw.series.number1722de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedingsArtificial Life and Evolutionary Computationde_CH
zhaw.funding.zhawHyperboostde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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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.


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