Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA.
J Intern Med. 2012 Feb;271(2):122-30. doi: 10.1111/j.1365-2796.2011.02491.x.
We present a vision for a Biomedical Cloud that draws on progress in the fields of Genomics, Systems Biology and biomedical data mining. The successful fusion of these areas will combine the use of biomarkers, genetic variants, and environmental variables to build predictive models that will drastically increase the specificity and timeliness of diagnosis for a wide range of common diseases, whilst delivering accurate predictions about the efficacy of treatment options. However, the amount of data being generated by each of these fields is staggering, as is the task of managing and analysing it. Adequate computing infrastructure needs to be developed to assemble, manage and mine the enormous and rapidly growing corpus of 'omics' data along with clinical information. We have now arrived at an intersection point between genome technology, cloud computing and biological data mining. This intersection point provides a launch pad for developing a globally applicable cloud computing platform capable of supporting a new paradigm of data intensive, cloud-enabled predictive medicine.
我们提出了一个生物医学云的愿景,该愿景借鉴了基因组学、系统生物学和生物医学数据挖掘领域的进展。这些领域的成功融合将结合使用生物标志物、遗传变异和环境变量来构建预测模型,从而极大地提高各种常见疾病的诊断特异性和及时性,同时对治疗方案的疗效做出准确预测。然而,这些领域产生的数据量非常庞大,管理和分析这些数据的任务也非常艰巨。需要开发足够的计算基础设施,以组装、管理和挖掘庞大且快速增长的“组学”数据以及临床信息。我们现在已经到达了基因组技术、云计算和生物数据挖掘的交叉点。这个交叉点为开发一个能够支持数据密集型、云启用的预测医学新范例的全球适用的云计算平台提供了一个起点。