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Brief Bioinform. 2019 May 21;20(3):1057-1062. doi: 10.1093/bib/bbx160.

Community effort endorsing multiscale modelling, multiscale data science and multiscale computing for systems medicine.

Author information

1
Universidade Nove de Lisboa.
2
Faculty for Computer Science and Engineering, University Ss. Cyril and Methodius in Skopje.
3
Microbiology at University of Ljubljana, Slovenia.
4
Virtual Physiological Human Institute.
5
Systems Tumor Immunology at the FAU Erlangen-Nuremberg, Germany.
6
Network biology, systems medicine and theoretical immunology.
7
Complex systems andmathematical biology.
8
Simulation and Modelling at Brunel University London.
9
Computer Science at Ulster University, United Kingdom.
10
Computational Biomedicine, University of Southern Denmark.
11
Inflammation, cardiovascular diseases and cancer, at molecular, cellular and clinical levels.
12
Medical University of Vienna.
13
Section for Science of Complex Systems at the Medical University of Vienna.
14
University of Ljubljana, Faculty of Medicine.
15
Target discovery and drug development.

Abstract

Systems medicine holds many promises, but has so far provided only a limited number of proofs of principle. To address this road block, possible barriers and challenges of translating systems medicine into clinical practice need to be identified and addressed. The members of the European Cooperation in Science and Technology (COST) Action CA15120 Open Multiscale Systems Medicine (OpenMultiMed) wish to engage the scientific community of systems medicine and multiscale modelling, data science and computing, to provide their feedback in a structured manner. This will result in follow-up white papers and open access resources to accelerate the clinical translation of systems medicine.

KEYWORDS:

computing; data science; modelling; systems medicine

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