Allen Discovery Center at Tufts University, Medford, MA 02155, USA.
Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ 85281, USA.
Int J Mol Sci. 2022 Aug 24;23(17):9580. doi: 10.3390/ijms23179580.
There is a growing appreciation in the fields of cell biology and developmental biology that cells collectively process information in time and space. While many powerful molecular tools exist to observe biophysical dynamics, biologists must find ways to quantitatively understand these phenomena at the systems level. Here, we present a guide for the application of well-established information theory metrics to biological datasets and explain these metrics using examples from cell, developmental and regenerative biology. We introduce a novel computational tool named after its intended purpose, calcium imaging, (CAIM) for simple, rigorous application of these metrics to time series datasets. Finally, we use CAIM to study calcium and cytoskeletal actin information flow patterns between embryonic animal cap stem cells. The tools that we present here should enable biologists to apply information theory to develop a systems-level understanding of information processing across a diverse array of experimental systems.
细胞生物学和发育生物学领域越来越认识到，细胞在时间和空间上共同处理信息。虽然存在许多强大的分子工具来观察生物物理动力学，但生物学家必须找到方法在系统水平上定量理解这些现象。在这里，我们介绍了一种应用信息论度量标准的指南，并通过来自细胞、发育和再生生物学的示例解释了这些度量标准。我们引入了一种新的计算工具，名为钙成像信息理论分析（CAIM），用于简单、严格地将这些度量标准应用于时间序列数据集。最后，我们使用 CAIM 研究胚胎动物帽干细胞之间的钙和细胞骨架肌动蛋白信息流模式。我们在这里提出的工具应该使生物学家能够应用信息论来发展对各种实验系统中信息处理的系统水平理解。
