The art and practice of systems biology in medicine: Mapping patterns of relationships
The art and practice of systems biology in medicine: Mapping patterns of relationships
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DOI：
10.1021/pr0606530
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发表时间：
2007-01-01
影响因子：
4.4
通讯作者：
McBurney, R. N.
中科院分区：
文献类型：
--
作者：
van der Greef, J.;Martin, S.;McBurney, R. N.
近年来，系统生物学已经从一个技术驱动的企业发展成为生命科学的一个新的战略工具，特别是在创新药物发现和药物开发方面。将终极系统表型与生物分子机制的深入研究相结合，将使我们对疾病病理学的理解发生革命，并将推动转化医学、联合疗法、中西医结合和个性化医学的发展。获得这种系统方法的好处的先决条件是一个可靠的、经过充分验证的生物分析平台，跨越互补的测量模式，特别是转录组学、蛋白质组学和代谢组学，与大变量综合生物统计学/生物信息学平台协同工作。适用的生物分析方法必须经历一个激烈的发展轨迹，才能在日常实践中达到可靠性能和定量可重复性的最佳水平。此外，为了产生这样的系统信息，必须基于对所创建的大型数据集的复杂性和统计特征的理解来设计实验。通过相关网络评估系统内的分子连通性，通过监测系统的动力学，或通过测量系统对诸如药物管理或挑战测试等扰动的反应，可以获得对生物学和系统科学的新见解。此外，可以通过相关网络分析来研究跨室通信和控制/反馈机制。所有这些数据分析都依赖于高质量生物分析平台数据集的生成。本文的重点是我们开发的生物分析平台的特点，以生成这样的数据集。讨论了系统生物学在药物研究和开发中的广泛适用性，并举例说明了疾病生物标志物研究、使用系统反应监测的药理学和跨室系统毒理学评估。
Systems biology has developed in recent years from a technology-driven enterprise to a new strategic tool in Life Sciences, particularly for innovative drug discovery and drug development. Combining the ultimate in systems phenotyping with in-depth investigations of biomolecular mechanisms will enable a revolution in our understanding of disease pathology and will advance translational medicine, combination therapies, integrative medicine, and personalized medicine. A prerequisite for deriving the benefits of such a systems approach is a reliable and well-validated bioanalytical platform across complementary measurement modalities, especially transcriptomics, proteomics, and metabolomics, that operates in concert with a megavariate integrative biostatistical/bioinformatics platform. The applicable bioanalytical methodologies must undergo an intense development trajectory to reach an optimal level of reliable performance and quantitative reproducibility in daily practice. Moreover, to generate such enabling systems information, it is essential to design experiments based on an understanding of the complexity and statistical characteristics of the large data sets created. Novel insights into biology and system science can be obtained by evaluating the molecular connectivity within a system through correlation networks, by monitoring the dynamics of a system, or by measuring the system responses to perturbations such as drug administration or challenge tests. In addition, cross-compartment communication and control/feed-back mechanisms can be studied via correlation network analyses. All these data analyses depend critically upon the generation of high-quality bioanalytical platform data sets. The emphasis of this paper is on the characteristics of a bioanalytical platform that we have developed to generate such data sets. The broad applicability of Systems Biology in pharmaceutical research and development is discussed with examples in disease biomarker research, in pharmacology using system response monitoring, and in cross-compartment system toxicology assessment.