Programmable models of growth and mutation of cancer-cell populations

In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint Programming, a flexible stochastic modelling language. The methodo...

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Vydané v:Electronic proceedings in theoretical computer science Ročník 67; číslo Proc. CompMod 2011; s. 19 - 33
Hlavní autori: Bortolussi, Luca, Policriti, Alberto
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Open Publishing Association 10.09.2011
ISSN:2075-2180, 2075-2180
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Abstract In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint Programming, a flexible stochastic modelling language. The methodology is tested on (and partially motivated by) the study of prostate cancer. In particular, we prove how our method is suitable to systematically reconstruct different mathematical models of prostate cancer growth --together with interactions with different kinds of hormone therapy-- at different levels of refinement.
AbstractList In this paper we propose a systematic approach to construct mathematical models describing populations of cancer-cells at different stages of disease development. The methodology we propose is based on stochastic Concurrent Constraint Programming, a flexible stochastic modelling language. The methodology is tested on (and partially motivated by) the study of prostate cancer. In particular, we prove how our method is suitable to systematically reconstruct different mathematical models of prostate cancer growth --together with interactions with different kinds of hormone therapy-- at different levels of refinement.
Author Bortolussi, Luca
Policriti, Alberto
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