竞争模型中肿瘤的生长速率、生长曲线及生长预测

IF 1.8 4区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Mahdi Sohrabi-Haghighat, Atefeh Deris
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引用次数: 0

摘要

癌症的生长仍然是科学界许多研究工作的焦点。到目前为止,已经引入了各种模型来分析癌症的行为,包括数学增长模型,如Logistic, Gompertz和Bertalany。尽管对癌症行为的分析取得了进展,但缺乏对癌症疾病的明确治疗表明需要有更多生物学背景支持的新观点。最近,有人提出了一个模型,在这个模型中,肿瘤的生长被解释为健康细胞和癌细胞在可用的氧气、营养物质和空间上竞争的结果。我们对该模型进行了修改,以便为该模型在肿瘤生长速率、生长曲线和生长预测中的更广泛应用提供必要的准备。同时,对一些实验数据进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Growth rate, growth curve and growth prediction of tumour in the competitive model
ABSTRACT The growth of cancer is still the focus of many research works in the scientific community. So far, various models have been introduced to analyse the behaviour of cancers, including the mathematical growth models such as Logistic, Gompertz and Bertalany. Despite the advances in the analysis of the cancer behaviour, the lack of definitive treatment of cancer disease indicates the need for new perspectives which are supported by more biological background. Recently, a model has been proposed, in which, the tumour growth is interpreted as the outcome of the competition of healthy and cancer cells over the available oxygen, nutrients and space. We have modified this model in order to provide the necessary preparations for wider use of the model in growth rate, growth curve and growth prediction of tumours. Meanwhile, the model is performed on some experimental data to show its capabilities.
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来源期刊
CiteScore
3.80
自引率
5.30%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.
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