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1.
Methods Mol Biol ; 1386: 375-404, 2016.
Artigo em Inglês | MEDLINE | ID: mdl-26677192

RESUMO

Systems medicine is the application of systems biology concepts, methods, and tools to medical research and practice. It aims to integrate data and knowledge from different disciplines into biomedical models and simulations for the understanding, prevention, cure, and management of complex diseases. Complex diseases arise from the interactions among disease-influencing factors across multiple levels of biological organization from the environment to molecules. To tackle the enormous challenges posed by complex diseases, we need a modeling and simulation framework capable of capturing and integrating information originating from multiple spatiotemporal and organizational scales. Multiscale modeling and simulation in systems medicine is an emerging methodology and discipline that has already demonstrated its potential in becoming this framework. The aim of this chapter is to present some of the main concepts, requirements, and challenges of multiscale modeling and simulation in systems medicine.


Assuntos
Anatomia , Simulação por Computador , Medicina , Modelos Biológicos , Fisiologia , Biologia de Sistemas , Sistemas de Gerenciamento de Base de Dados , Humanos , Gestão da Informação , Medicina/métodos , Biologia de Sistemas/métodos
2.
Philos Trans A Math Phys Eng Sci ; 372(2021)2014 Aug 06.
Artigo em Inglês | MEDLINE | ID: mdl-24982249

RESUMO

We review a methodology to design, implement and execute multi-scale and multi-science numerical simulations. We identify important ingredients of multi-scale modelling and give a precise definition of them. Our framework assumes that a multi-scale model can be formulated in terms of a collection of coupled single-scale submodels. With concepts such as the scale separation map, the generic submodel execution loop (SEL) and the coupling templates, one can define a multi-scale modelling language which is a bridge between the application design and the computer implementation. Our approach has been successfully applied to an increasing number of applications from different fields of science and technology.

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