Noble Denis
University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK.
Science. 2002 Mar 1;295(5560):1678-82. doi: 10.1126/science.1069881.
Successful physiological analysis requires an understanding of the functional interactions between the key components of cells, organs, and systems, as well as how these interactions change in disease states. This information resides neither in the genome nor even in the individual proteins that genes code for. It lies at the level of protein interactions within the context of subcellular, cellular, tissue, organ, and system structures. There is therefore no alternative to copying nature and computing these interactions to determine the logic of healthy and diseased states. The rapid growth in biological databases; models of cells, tissues, and organs; and the development of powerful computing hardware and algorithms have made it possible to explore functionality in a quantitative manner all the way from the level of genes to the physiological function of whole organs and regulatory systems. This review illustrates this development in the case of the heart. Systems physiology of the 21st century is set to become highly quantitative and, therefore, one of the most computer-intensive disciplines.
成功的生理学分析需要了解细胞、器官和系统的关键组成部分之间的功能相互作用,以及这些相互作用在疾病状态下如何变化。这些信息既不存在于基因组中,甚至也不存在于基因编码的单个蛋白质中。它存在于亚细胞、细胞、组织、器官和系统结构背景下的蛋白质相互作用层面。因此,除了模仿自然并计算这些相互作用以确定健康和疾病状态的逻辑之外,别无他法。生物数据库、细胞、组织和器官模型的快速增长,以及强大的计算硬件和算法的发展,使得从基因层面到整个器官和调节系统的生理功能,以定量方式探索功能成为可能。本综述以心脏为例说明了这一发展。21世纪的系统生理学将变得高度定量,因此将成为计算量最大的学科之一。