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NPJ Syst Biol Appl. 2018 Jun 2;4:21. doi: 10.1038/s41540-018-0059-y. eCollection 2018.

Systems medicine disease maps: community-driven comprehensive representation of disease mechanisms.

Author information

1
1European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007 Lyon, France.
2
2Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7 Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg.
3
3Institut Curie, Paris, France.
4
4INSERM, U900 Paris, France.
5
5Mines ParisTech, Fontainebleau, France.
6
6PSL Research University, Paris, France.
7
7Northern Ireland Centre for Stratified Medicine, Ulster University, C-Tric, Altnagelvin Hospital Campus, Derry, Co Londonderry, Northern Ireland, BT47 6SB UK.
8
8The Babraham Institute, Babraham Research Campus, Cambridge, CB22 3AT UK.
9
Department of Infection and Immunity, Luxembourg Institute of Health (LIH), House of BioHealth, 29 Rue Henri Koch, L-4354 Esch-Sur-Alzette, Luxembourg.
10
10Institute for Advanced Biosciences, University Grenoble-Alpes-INSERM U1209-CNRS UMR5309, Site Santé - Allée des Alpes, 38700 La Tronche, France.
11
11Department of Dermatology and Allergy Center, Odense Research Center for Anaphylaxis, University of Southern Denmark, Odense, Denmark.
12
12Faculty of Engineering, Computer Engineering Department, Bilkent University, Ankara, 06800 Turkey.

Abstract

The development of computational approaches in systems biology has reached a state of maturity that allows their transition to systems medicine. Despite this progress, intuitive visualisation and context-dependent knowledge representation still present a major bottleneck. In this paper, we describe the Disease Maps Project, an effort towards a community-driven computationally readable comprehensive representation of disease mechanisms. We outline the key principles and the framework required for the success of this initiative, including use of best practices, standards and protocols. We apply a modular approach to ensure efficient sharing and reuse of resources for projects dedicated to specific diseases. Community-wide use of disease maps will accelerate the conduct of biomedical research and lead to new disease ontologies defined from mechanism-based disease endotypes rather than phenotypes.

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