Publication:
Mathematical and Numerical Modelling of Interference of Immune Cells in the Tumour Environment

dc.authorscopusid57365071800
dc.authorscopusid57202809964
dc.authorscopusid10639356300
dc.authorwosidSinha, Sweta/Jts-3573-2023
dc.authorwosidSingh, Paramjeet/Jxl-6437-2024
dc.authorwosidKöksal, Mehmet/Aag-3612-2021
dc.contributor.authorSinha, Sweta
dc.contributor.authorSingh, Paramjeet
dc.contributor.authorKoksal, Mehmet Emir
dc.contributor.authorIDSingh, Paramjeet/0000-0002-8641-0785
dc.contributor.authorIDSinha, Sweta/0000-0002-9291-8390
dc.date.accessioned2025-12-11T01:21:23Z
dc.date.issued2023
dc.departmentOndokuz Mayıs Üniversitesien_US
dc.department-temp[Sinha, Sweta; Singh, Paramjeet] Thapar Inst Engn & Technol, Sch Math, Patiala, India; [Koksal, Mehmet Emir] Ondokuz Mayis Univ, Dept Math, Samsun, Turkiye; [Koksal, Mehmet Emir] Univ Twente, Dept Appl Math, Enschede, Netherlandsen_US
dc.descriptionSingh, Paramjeet/0000-0002-8641-0785; Sinha, Sweta/0000-0002-9291-8390;en_US
dc.description.abstractIn this article, the behaviour of tumour growth and its interaction with the immune system have been studied using a mathematical model in the form of partial differential equations. However, the development of tumours and how they interact with the immune system make up an extremely complex and little-understood system. A new mathematical model has been proposed to gain insight into the role of immune response in the tumour microenvironment when no treatment is applied. The resulting model is a set of partial differential equations made up of four variables: the population density of tumour cells, two different types of immune cells (CD4+ helper T cells and CD8+ cytotoxic T cells), and nutrition content. Such kinds of systems also occur frequently in science and engineering. The interaction of tumour and immune cells is exemplified by predator-prey models in ecology, in which tumour cells act as prey and immune cells act as predators. The tumour-immune cell interaction is expressed via Holling's Type-III and Beddington-DeAngelis functional responses. The combination of finite volume and finite element method is used to approximate the system numerically because these approximations are more suitable for time-dependent systems having diffusion. Finally, numerical simulations show that the methods perform well and depict the behaviour of the model.en_US
dc.description.woscitationindexScience Citation Index Expanded
dc.identifier.doi10.1155/2023/9006678
dc.identifier.issn1026-0226
dc.identifier.issn1607-887X
dc.identifier.scopus2-s2.0-85146591355
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1155/2023/9006678
dc.identifier.urihttps://hdl.handle.net/20.500.12712/43177
dc.identifier.volume2023en_US
dc.identifier.wosWOS:000915119400001
dc.identifier.wosqualityQ3
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofDiscrete Dynamics in Nature and Societyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleMathematical and Numerical Modelling of Interference of Immune Cells in the Tumour Environmenten_US
dc.typeArticleen_US
dspace.entity.typePublication

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