King's College, Cambridge, UK.
Philos Trans R Soc Lond B Biol Sci. 2010 Jan 12;365(1537):207-12. doi: 10.1098/rstb.2009.0221.
The conversion of data into knowledge constitutes a great challenge for future biological research. The new science of Systems Biology claims to be able to solve the problem but I contend that this approach will fail because deducing models of function from the behaviour of a complex system is an inverse problem that is impossible to solve. In addition, one cannot easily escape into high-level holistic approaches, since the essence of all biological systems is that they are encoded as molecular descriptions in their genes and since genes are molecules and exert their functions through other molecules, the molecular explanation must constitute the core of understanding biological systems. We then solve the forward problem of computing the behaviour of the system from its components and their interactions. I propose that the correct level of abstraction is the cell and provide an outline of CELLMAP, a design for a system to organize biological information.
数据到知识的转化对未来的生物学研究构成了巨大的挑战。系统生物学这门新科学声称能够解决这个问题，但我认为这种方法将会失败，因为从复杂系统的行为中推导出功能模型是一个不可能解决的逆问题。此外，人们不可能轻易地逃避到高层次的整体方法中，因为所有生物系统的本质都是它们被编码在基因中的分子描述，并且由于基因是分子，它们通过其他分子发挥其功能，因此分子解释必须构成理解生物系统的核心。然后，我们从系统的组成部分及其相互作用出发，解决系统行为的正向问题。我提出正确的抽象层次是细胞，并提供了 CELLMAP 的概述，这是一个组织生物信息的系统设计。
