Sinha Anirban, Sterk Peter J
Department of Respiratory Medicine, F5-158, Academic Medical Centre, University of Amsterdam, Meibergdreef 9, 1100 AZ, Amsterdam, The Netherlands.
Clin Transl Med. 2017 Oct 27;6(1):39. doi: 10.1186/s40169-017-0170-5.
Clinical disease phenotypes with underlying information of molecular and biological signatures for the same, is a prerequisite for improving medical care and developing more effective, stratified management strategies. This commentary reviews the research carried out by Cao et al. to unravel biological networks associated with different clinical categories of asthma. It finally comments on the utility of using data from multiple platforms aided by integrated systems approaches to effectively find out the obvious underlying physiological disease signatures related to clinical disease sub-types.
对于相同的临床疾病表型具备潜在的分子和生物学特征信息，是改善医疗护理以及制定更有效分层管理策略的前提条件。本述评回顾了曹等人开展的研究，以揭示与哮喘不同临床类别相关的生物网络。最后，本述评对借助综合系统方法利用来自多个平台的数据以有效找出与临床疾病亚型相关的明显潜在生理疾病特征的效用进行了评论。
