Environment and Health Department, Istituto Superiore di Sanità, Viale Regina Elena 299, Roma, Italy.
BMC Genomics. 2010 Feb 10;11 Suppl 1(Suppl 1):S2. doi: 10.1186/1471-2164-11-S1-S2.
The interaction of a multiplicity of scales in both time and space is a fundamental feature of biological systems. The complementation of macroscopic (entire organism) and microscopic (molecular biology) views with a mesoscopic level of analysis able to connect the different planes of investigation is urgently needed. This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.
The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems. Here we show the application of this paradigm to different systems going from yeast metabolism to murine macrophages response to immune stimulation.
The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.
在时间和空间上,多种尺度的相互作用是生物系统的一个基本特征。急需用能够连接不同研究层面的介观分析来补充宏观(整个生物体)和微观(分子生物学)的观点,这将使我们既能获得一个合理化高通量技术带来的大量数据的一般参考框架,又能对生物系统得出有效的操作观点。
网络范式中,微观水平的元素(节点)通过功能链接相互关联,从而产生全局(整个网络)和局部(特定)行为,这是尝试开发受统计力学启发的生物系统方法的一个有前途的隐喻。在这里,我们展示了该范式在从酵母代谢到鼠巨噬细胞对免疫刺激的反应等不同系统中的应用。
需要用介观方法来补充纯粹的分子观点,这在所有被研究的例子中都是显而易见的,反过来又证明了在分子生物学中占主导地位的简单遍历方法是站不住脚的,在这种方法中,来自大量细胞的大量数据被认为是相对于单个“平均”细胞的。