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整合组学技术以在系统层面研究肺生理学和病理学。

Integrating omics technologies to study pulmonary physiology and pathology at the systems level.

作者信息

Pathak Ravi Ramesh, Davé Vrushank

机构信息

Morsani College of Medicine, Department of Pathology and Cell Biology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

出版信息

Cell Physiol Biochem. 2014;33(5):1239-60. doi: 10.1159/000358693. Epub 2014 Apr 28.

Abstract

Assimilation and integration of "omics" technologies, including genomics, epigenomics, proteomics, and metabolomics has readily altered the landscape of medical research in the last decade. The vast and complex nature of omics data can only be interpreted by linking molecular information at the organismic level, forming the foundation of systems biology. Research in pulmonary biology/medicine has necessitated integration of omics, network, systems and computational biology data to differentially diagnose, interpret, and prognosticate pulmonary diseases, facilitating improvement in therapy and treatment modalities. This review describes how to leverage this emerging technology in understanding pulmonary diseases at the systems level -called a "systomic" approach. Considering the operational wholeness of cellular and organ systems, diseased genome, proteome, and the metabolome needs to be conceptualized at the systems level to understand disease pathogenesis and progression. Currently available omics technology and resources require a certain degree of training and proficiency in addition to dedicated hardware and applications, making them relatively less user friendly for the pulmonary biologist and clinicians. Herein, we discuss the various strategies, computational tools and approaches required to study pulmonary diseases at the systems level for biomedical scientists and clinical researchers.

摘要

在过去十年中,包括基因组学、表观基因组学、蛋白质组学和代谢组学在内的“组学”技术的融合与整合已经显著改变了医学研究的格局。组学数据的海量和复杂性只能通过在生物体水平上关联分子信息来解读,这构成了系统生物学的基础。肺部生物学/医学研究需要整合组学、网络、系统和计算生物学数据,以便对肺部疾病进行鉴别诊断、解读和预测,促进治疗方法和治疗模式的改进。本综述描述了如何在系统层面利用这一新兴技术来理解肺部疾病,即所谓的“系统组学”方法。考虑到细胞和器官系统的运作整体性,需要在系统层面将患病的基因组、蛋白质组和代谢组概念化,以理解疾病的发病机制和进展。目前可用的组学技术和资源除了需要专用硬件和应用程序外,还需要一定程度的培训和熟练操作能力,这使得它们对肺部生物学家和临床医生来说相对不太容易使用。在此,我们讨论了生物医学科学家和临床研究人员在系统层面研究肺部疾病所需的各种策略、计算工具和方法。

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