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Metastatik tümör büyümesinin dinamik modelleri

Dynamic models of metastatic tumor growth
Authors: Zor, Hatice;

Metastatik tümör büyümesinin dinamik modelleri

Abstract

Bu tezde, kanser biyolojisine ve tedavisine kısa bir giriş, metastatik kanserin yayılımını ve kanser karşıtı ilaçların farklı dozlarına nasıl tepki verebileceğini tanımlamak için matematiksel popülasyon dinamikleri modellerinin kullanımı üzerine odaklanılarak sunulmaktadır. Bu çerçevede, tek tümörlü büyüme modellerinin analitik çözümleri, popülasyon dinamiği modelleri ve popülasyon dinamikleri sistemlerini incelemek için analitik yaklaşımlar düşünülmektedir.

In this thesis, a brief introduction to cancer biology and treatment is presented with a focus on the use of mathematical population dynamics models to describe the spread of metastatic cancer and how it could respond to different dosing of anti-cancer drugs. Within this framework, analytical solutions of single-tumor growth models, population dynamics models and analytical approaches for studying the population dynamics systems are considered.

77

Country
Turkey
Related Organizations
Keywords

Matematik, Single Tumor Growth, Biological Modelling, Metastaz, 530, Metastatic Tumor, 510, Metastasis, Metastatik Tümör, Tek Tümör Büyümesi, Biyolojik Modelleme, Mathematical Modelling, Matematiksel Modelleme, Popülasyon Dinamikleri Modelleri, Population Dynamics Models, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities
Cancer Research