Werbin Jeffrey L, Heinz William F, Romer Lewis H, Hoh Jan H
Department of Physiology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
Langmuir. 2007 Oct 23;23(22):10883-6. doi: 10.1021/la701605s. Epub 2007 Sep 22.
One powerful approach to understanding how cells process spatially variant signals is based on using micropatterned substrates to control the distribution of signaling molecules. However, quantifying spatially complex signals requires an appropriate metric. Here we propose that the Shannon information theory formalism provides a robust and useful way to quantify the organization of proteins in micropatterned systems. To demonstrate the use of informational entropy as a metric, we produced patterns of lines of fibronectin with varying information content. Fibroblasts grown on these patterns were sensitive to very small changes in informational entropy (6.6 bits), and the responses depended on the scale of the pattern.
一种理解细胞如何处理空间变异信号的有效方法是基于使用微图案化底物来控制信号分子的分布。然而,量化空间复杂信号需要一个合适的指标。在这里,我们提出香农信息理论形式体系提供了一种强大且有用的方法来量化微图案化系统中蛋白质的组织。为了证明信息熵作为一种指标的用途,我们生成了具有不同信息含量的纤连蛋白线条图案。在这些图案上生长的成纤维细胞对信息熵的非常小的变化(6.6比特)敏感,并且反应取决于图案的尺度。