In this work we present a new approach, based on an evolution of the mean field analysis that exploits some of the features of the “Markovian agents” performance evaluation formalisms. This new technique allows to study the system evolution through a sound analytical treatment of the spatial dependency. In particular, we focus on the study of tumor progression, showing that the growth and progression of many cancers are driven by small groups of Cancer Stem Cells (CSCs).

An analytical spatially-based approach to study cancer cell population evolutions / F. Cordero ; M. Gribaudo; D. Manini. - In: EMBNET NEWS. - ISSN 1023-4144. - Supplemento A(2012), pp. 27-27. ((Intervento presentato al convegno 9th Annual Meeting of the Italian Society of Bioinformatics (BITS) tenutosi a Catania nel 2/5/2012.

An analytical spatially-based approach to study cancer cell population evolutions

CORDERO, Francesca;MANINI, DANIELE
2012

Abstract

In this work we present a new approach, based on an evolution of the mean field analysis that exploits some of the features of the “Markovian agents” performance evaluation formalisms. This new technique allows to study the system evolution through a sound analytical treatment of the spatial dependency. In particular, we focus on the study of tumor progression, showing that the growth and progression of many cancers are driven by small groups of Cancer Stem Cells (CSCs).
9th Annual Meeting of the Italian Society of Bioinformatics (BITS)
Catania
2/5/2012
Supplemento A
27
27
Cancer stem cells model; Markovian Agents
F. Cordero ; M. Gribaudo; D. Manini
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/102293
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