Abstract:
Cell responses are usually viewed as transitive events with fixed inputs and outputs that are regulated by feedback loops. In contrast, directed cycles (DCs) have all nodes connected, and the flow is in a single direction. Consequently, DCs can regenerate themselves and implement intransitive logic. DCs are able to couple unrelated chemical reactions to each edge. The output depends upon which node is used as input. DCs can also undergo selection to minimize the loss of thermodynamic entropy while maximizing the gain of information entropy. The intransitive logic underlying DCs enhances their programmability and impacts their evolution. The natural selection of DCs favors the persistence, adaptability, and self-awareness of living organisms and does not depend solely on changes to coding sequences. Rather, the process can be RNA-directed. I use flipons, nucleic acid sequences that change conformation under physiological conditions, as a simple example and then describe more complex DCs. Flipons are often encoded by repeats and greatly increase the Kolmogorov complexity of genomes by adopting alternative structures. Other DCs allow cells to regenerate, recalibrate, reset, repair, and rewrite themselves, going far beyond the capabilities of current computational devices. Unlike Turing machines, cells are not designed to halt but rather to regenerate.
摘要:
细胞响应通常被视为具有由反馈回路调节的固定输入和输出的传递事件。相比之下,有向循环(DC)连接所有节点,流动是单向的。因此,DC可以自我再生并实现非传递性逻辑。DC能够将不相关的化学反应耦合到每个边缘。输出取决于使用哪个节点作为输入。DC还可以经历选择以最小化热力学熵的损失,同时最大化信息熵的增益。DC底层的不可传递逻辑增强了它们的可编程性并影响它们的进化。DC的自然选择有利于持久性,适应性,和生物体的自我意识,并不仅仅取决于编码序列的变化。相反,该过程可以是RNA指导的。我用动画,在生理条件下改变构象的核酸序列,作为一个简单的例子,然后描述更复杂的DC。Flipons通常由重复编码,并通过采用替代结构大大增加了基因组的Kolmogorov复杂性。其他DC允许细胞再生,重新校准,重置,修复,重写自己,远远超出了当前计算设备的能力。不像图灵机,细胞的设计不是停止,而是再生。