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- W4205364108 abstract "In this study we review the current state of the art for Dupuytren's disease (DD), while emphasising the need for a better integration of clinical, experimental and quantitative predictive approaches to understand the evolution of the disease and improve current treatments. We start with a brief review of the biology of this disease and current treatment approaches. Then, since certain aspects in the pathogenesis of this disorder have been compared to various biological aspects of wound healing and malignant processes, next we review some in silico (mathematical modelling and simulations) predictive approaches for complex multi-scale biological interactions occurring in wound healing and cancer. We also review the very few in silico approaches for DD, and emphasise the applicability of these approaches to address more biological questions related to this disease. We conclude by proposing new mathematical modelling and computational approaches for DD, which could be used in the absence of animal models to make qualitative and quantitative predictions about the evolution of this disease that could be further tested in vitro." @default.
- W4205364108 created "2022-01-26" @default.
- W4205364108 creator A5006689072 @default.
- W4205364108 creator A5058102813 @default.
- W4205364108 creator A9999999999 @default.
- W4205364108 date "2022-01-01" @default.
- W4205364108 modified "2023-10-14" @default.
- W4205364108 title "Quantitative predictive approaches for Dupuytren disease: a brief review and future perspectives" @default.
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