Multiscale computing in systems medicine: a brief reflection
Date Issued
2018-12-03
Author(s)
Zheng, Huiru
Talreja Wassan, Jyotsna
Alexandru Moisescu, Mihnea
Stoicu-Tivadar, Lacramioara
Miranda, João
Crisan-Vida, Mihaela
Stefan Sacala, Ioan
Badnjevic, Almir
Abstract
Today’s modelling approaches in Systems
Medicine are increasingly multiscale, containing two or more
submodels, where each operates on different temporal and/or
spatial scales. In addition, as these models become increasingly
sophisticated, they tend to be run as multiscale computing
applications using computational infrastructures such as
clusters, supercomputers, grids or clouds. Constructing,
validating and deploying such applications is far from trivial,
and communities in different scientic disciplines have chosen
very diverse approaches to address these challenges. Within this
paper we reect on the use of Multiscale Computing within the
context of Systems Medicine. Multiscale Computing is widely
applied within this area, and instead of summarizing the eld as
a whole we will highlight a set of challenges that we believe are
of key relevance to the Systems Medicine community.
Medicine are increasingly multiscale, containing two or more
submodels, where each operates on different temporal and/or
spatial scales. In addition, as these models become increasingly
sophisticated, they tend to be run as multiscale computing
applications using computational infrastructures such as
clusters, supercomputers, grids or clouds. Constructing,
validating and deploying such applications is far from trivial,
and communities in different scientic disciplines have chosen
very diverse approaches to address these challenges. Within this
paper we reect on the use of Multiscale Computing within the
context of Systems Medicine. Multiscale Computing is widely
applied within this area, and instead of summarizing the eld as
a whole we will highlight a set of challenges that we believe are
of key relevance to the Systems Medicine community.
Subjects
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