Saqi Mansoor, Pellet Johann, Roznovat Irina, Mazein Alexander, Ballereau Stéphane, De Meulder Bertrand, Auffray Charles
European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, 50 Avenue Tony Garnier, Lyon, 69007, France.
Université Claude Bernard, 3e étage plot 2, 50 Avenue Tony Garnier, Lyon, Cedex 07, 69366, France.
Methods Mol Biol. 2016;1386:43-60. doi: 10.1007/978-1-4939-3283-2_3.
Recent advances in genomics have led to the rapid and relatively inexpensive collection of patient molecular data including multiple types of omics data. The integration of these data with clinical measurements has the potential to impact on our understanding of the molecular basis of disease and on disease management. Systems medicine is an approach to understanding disease through an integration of large patient datasets. It offers the possibility for personalized strategies for healthcare through the development of a new taxonomy of disease. Advanced computing will be an important component in effectively implementing systems medicine. In this chapter we describe three computational challenges associated with systems medicine: disease subtype discovery using integrated datasets, obtaining a mechanistic understanding of disease, and the development of an informatics platform for the mining, analysis, and visualization of data emerging from translational medicine studies.
基因组学的最新进展使得能够快速且相对廉价地收集患者分子数据，包括多种组学数据。将这些数据与临床测量结果相结合，有可能影响我们对疾病分子基础的理解以及疾病管理。系统医学是一种通过整合大型患者数据集来理解疾病的方法。它通过开发新的疾病分类法，为个性化医疗策略提供了可能性。先进的计算将是有效实施系统医学的重要组成部分。在本章中，我们描述了与系统医学相关的三个计算挑战：使用整合数据集发现疾病亚型、获得对疾病的机制性理解，以及开发一个用于挖掘、分析和可视化转化医学研究中产生的数据的信息学平台。
