Noble D
University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, UK.
Biochem Soc Trans. 2005 Jun;33(Pt 3):539-42. doi: 10.1042/BST0330539.
Understanding the logic of living systems requires knowledge of the mechanisms involved at the levels at which functionality is expressed. This information resides neither in the genome, nor even in the individual proteins that genes code for. No functionality is expressed at these levels. It emerges as the result of interactions between many proteins relating to each other in multiple cascades and in interaction with the cellular environment. 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. I use models of the heart to demonstrate that we can now go all the way from individual genetic information (on mutations, for example) to exploring the consequences at a whole-organ level.
理解生命系统的逻辑需要了解在功能得以表达的各个层面上所涉及的机制。这些信息既不存在于基因组中,甚至也不存在于基因所编码的单个蛋白质中。在这些层面上不会表达任何功能。功能是许多蛋白质之间在多个级联中相互关联并与细胞环境相互作用的结果。因此,除了复制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、组织和器官模型的迅速增长,以及强大的计算硬件和算法的发展,使得从基因层面一直到整个器官和调节系统的生理功能,都能够以定量的方式探索功能成为可能。我利用心脏模型来证明,我们现在能够从个体遗传信息(例如关于突变的信息)一路探索到整个器官层面的后果。