Mazein Alexander, Ostaszewski Marek, Kuperstein Inna, Watterson Steven, Le Novère Nicolas, Lefaudeux Diane, De Meulder Bertrand, Pellet Johann, Balaur Irina, Saqi Mansoor, Nogueira Maria Manuela, He Feng, Parton Andrew, Lemonnier Nathanaël, Gawron Piotr, Gebel Stephan, Hainaut Pierre, Ollert Markus, Dogrusoz Ugur, Barillot Emmanuel, Zinovyev Andrei, Schneider Reinhard, Balling Rudi, Auffray Charles
1European Institute for Systems Biology and Medicine, CIRI UMR5308, CNRS-ENS-UCBL-INSERM, Université de Lyon, 50 Avenue Tony Garnier, 69007 Lyon, France.
2Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, 7 Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg.
NPJ Syst Biol Appl. 2018 Jun 2;4:21. doi: 10.1038/s41540-018-0059-y. eCollection 2018.
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.
系统生物学中计算方法的发展已达到成熟状态，使其能够向系统医学转变。尽管取得了这一进展，但直观的可视化和依赖上下文的知识表示仍然是一个主要瓶颈。在本文中，我们描述了疾病图谱项目，这是一项致力于以社区驱动的方式对疾病机制进行计算机可读的全面表示的工作。我们概述了该计划成功所需的关键原则和框架，包括最佳实践、标准和协议的使用。我们采用模块化方法，以确保为致力于特定疾病的项目高效共享和重用资源。在全社区范围内使用疾病图谱将加速生物医学研究的开展，并导致从基于机制的疾病内型而非表型定义新的疾病本体。
