TY - JOUR
T1 - Systems medicine disease maps
T2 - community-driven comprehensive representation of disease mechanisms
AU - Mazein, Alexander
AU - Ostaszewski, Marek
AU - Kuperstein, Inna
AU - Watterson, Steven
AU - Le Novère, Nicolas
AU - Lefaudeux, Diane
AU - De Meulder, Bertrand
AU - Pellet, Johann
AU - Balaur, Irina
AU - Saqi, Mansoor
AU - Nogueira, Maria Manuela
AU - He, Feng
AU - Parton, Andrew
AU - Lemonnier, Nathanaël
AU - Gawron, Piotr
AU - Gebel, Stephan
AU - Hainaut, Pierre
AU - Ollert, Markus
AU - Dogrusoz, Ugur
AU - Barillot, Emmanuel
AU - Zinovyev, Andrei
AU - Schneider, Reinhard
AU - Balling, Rudi
AU - Auffray, Charles
N1 - Funding Information:
This work was supported by the CNRS, University of Luxembourg, Institut Curie and in part through the U-BIOPRED (IMI no. 115010 grant to C.A.) and eTRIKS (IMI no. 115446 grant to C.A., R.B. and R.S.) Consortia funded by the European Union and the European Federation of Pharmaceutical Industry Associations, the Coordinating action for the implementation of systems medicine in Europe (CASyM FP7 grant no. 305333 to C.A. and R.B.), the COLOSYS grant ANR-15-CMED-0001-04, provided by the Agence Nationale de la Recherche under the frame of ERACoSysMed-1, the ERA-Net for Systems Medicine in clinical research and medical practice (to I.K., E.B. and A.Z.). A. P. and S.W. acknowledge a research exchange grant from CASyM.
Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85051531983&partnerID=8YFLogxK
UR - https://pubmed.ncbi.nlm.nih.gov/29872544
U2 - 10.1038/s41540-018-0059-y
DO - 10.1038/s41540-018-0059-y
M3 - Article
C2 - 29872544
AN - SCOPUS:85051531983
SN - 2056-7189
VL - 4
JO - npj Systems Biology and Applications
JF - npj Systems Biology and Applications
IS - 1
M1 - 21
ER -