Metabolism, whose reprogramming is an established cancer hallmark, promotes growth and proliferation in cancer cells. Genome-wide metabolic models are becoming increasingly capable of describing cancer growth. Multiscale models may allow the capture of other relevant features of cancer cells and their relationship with the tumor microenvironment. The merging of multiscale metabolic modeling and artificial intelligence can lead to a paradigm shift in oncology, possibly leading to patient-specific personalized digital twins.

Vanoni, M., Palumbo, P., Busti, S., Alberghina, L. (2024). A critical review of multiscale modeling for predictive understanding of cancer cell metabolism. CURRENT OPINION IN SYSTEMS BIOLOGY, 39(December 2024) [10.1016/j.coisb.2024.100531].

A critical review of multiscale modeling for predictive understanding of cancer cell metabolism

Vanoni M.
;
Palumbo P.;Busti S.;Alberghina L.
2024

Abstract

Metabolism, whose reprogramming is an established cancer hallmark, promotes growth and proliferation in cancer cells. Genome-wide metabolic models are becoming increasingly capable of describing cancer growth. Multiscale models may allow the capture of other relevant features of cancer cells and their relationship with the tumor microenvironment. The merging of multiscale metabolic modeling and artificial intelligence can lead to a paradigm shift in oncology, possibly leading to patient-specific personalized digital twins.
Articolo in rivista - Articolo scientifico
Cancer metabolism; Mathematical modeling; Warburg effect;
English
20-lug-2024
2024
39
December 2024
100531
reserved
Vanoni, M., Palumbo, P., Busti, S., Alberghina, L. (2024). A critical review of multiscale modeling for predictive understanding of cancer cell metabolism. CURRENT OPINION IN SYSTEMS BIOLOGY, 39(December 2024) [10.1016/j.coisb.2024.100531].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/507423
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